Algorithm for wireless, motion and position-sensing, integrating radiation sensor for occupational and environmental dosimetry

The present invention relates to radiation metering systems and, in particular, to the accurate calculation of equivalents absorbed due to radiation exposure events.

Occupational radiation exposure events can occur in the healthcare, oil and gas industries, the military, and other industrial settings. There, the use of materials or devices that emit ionizing radiation can result in accidents or occupationally unavoidable exposure events.

An emergency radiation exposure event can occur when a radiological weapon (RDD), an improvised nuclear device (IND), or another source of radioactive material is released and contaminates a given area.

Radiation metering programs for occupational radiation exposure events, and emergency manegement plans for emergency radiation exposure events, monitor and protect workers or the general public who may have been exposed to radiation during radiation events. Developed to do.

An important aspect of the emergency management program following a radiation event is firefighting, police and other emergency responders (first responders), health workers and citizens who may have been exposed to radiation from radiological or nuclear weapons. It is to ensure the safety of. Often, radiation exposure of first responders and healthcare professionals is monitored at least partially using traditional radiation detection devices, but monitoring the exposure of potential tens of thousands of citizens is a more difficult problem. Is shown.

In addition, continuous external personal dosimetry monitoring for individual first responders and healthcare professionals and the general public may be required after removable contamination has been removed. Land restoration can be a long-term project, and in order to minimize social disruption, it may be necessary to allow residents access to areas before decontamination is complete. For example, allowing citizens to pass through areas with transit centers, highways or buildings can facilitate government work, commerce, family unity, routine medical care, and so on. As individuals travel through contaminated areas, it can be valuable to know the dose and duration of exposure at each location visited. Such dosimetry is a model-based dose assessment by providing a geographic map of the dynamic dose distribution reconstructed from a large number of dosimeters that collect dose event data across potentially still contaminated areas. Reliance on can be reduced and unnecessary regional restrictions can be avoided. Unlike decontamination of suburban waste facilities, where the public can be eliminated at almost no cost to society, in an urban environment time is important and elimination costs outweigh the benefits of avoiding exposure to relatively low radiation doses. Can be large. After decontamination, personal dosimetry could increase public confidence that the personal dose was below an acceptable threshold and the final decontamination was effective.

Several radiation measurement techniques exist recently, including TLD dosimeters, OSL dosimeters, electron dosimeters, quartz or carbon fiber electrets, and other solid-phase radiation metering devices.

Thermoluminescent dosimeter (TLD) badges are personal monitoring devices that use special materials (eg, lithium fluoride) that retain the stored energy from radiation. The TLD badge is loaded with heat to make the TLD material emit light. The light is detected by a TLD reader (calibrated to provide proportional current). A significant disadvantage of the TLD badge is that the device signal is cleared or zeroed during the read, and the dosimeter must be returned to the processing laboratory for the read, which is considerable to obtain a read. It takes time.

Optically Pumped Luminescence (OSL) badges use Photoexcited Luminescence Material (OSLM) (eg, aluminum oxide) to retain radiation energy. Small crystal traps in OSL materials trap and store energy from radiation exposure. The exposure dose is determined by illuminating the crystal trap with excitation light of one color (eg, green) and measuring the amount of light emitted by the other color (eg, blue). Alternatively, pulsed photoexcitation is used to distinguish between excitation light and light emission, as described, for example, in US Pat. Nos. 5,892,234 and 5,962,857, which are incorporated herein by reference in their entirety. Can be done. Unlike TLD systems, OSL systems provide reads in just seconds. And the dosimeter can be read many times because only a very small amount of the exposure signal is used up during the read. OSL dosimeters can be read outdoors using a small, outdoor-portable reader. However, this reader is still too large, slow, and expensive for individuals to read in real time outdoors. In existing OSL dosimetry programs for reporting recorded doses, dosimeters must be returned to the processing laboratory for retrieval.

For more information on OSL materials and systems, see: US Pat. No. 5,731,590 to Miller; US Pat. No. 6,846,434 to Akselrod; US Pat. No. 6,198,108 to Schwietzer et al.; US Pat. No. 6,198,108 to Yoder et al. No. 6,127,685; U.S. Patent Application No. 10 / 768,094 to Akselrod et al.; All of these are incorporated herein by reference in their entirety. See also: Lars Botter-Jensen et al., Optically Stimulated Luminescence Dosimetry, Elesevier, 2003; Klemic, G., Bailey, P., Miller, K., Monetti, M., "External radiation dosimetry in the aftermath" of radiological terrorist event ", Rad. Prot. Dosim, printing; Akslerod, MS, Kortov, VS, and Gorelova, E. A., "Preparation and properties of Al₂O₃: C ", Radial. Prot. Dosim. 47, 159-164 (1993); and Akselrod, MS, Lucas, AC, Polf, JC, McKeever, SWS" Optimically stimulated luminescence of Al₂O₃: C ", Radiation Measurements, 29, (3-4), 391-399 (1998). All of these are incorporated herein by reference in their entirety.

Solid phase sensors use solid phase materials such as semiconductors to collect charges in a semiconductor medium and quantify radiation interactions. As the radiation particles move through the semiconductor medium, electron holes are generated along the path of the particles. The movement of electron-hole pairs in the applied electric field produces a basic electrical signal from the detector. There are two main categories of solid phase sensors, active and passive. Active sensors often use semiconductors that are biased by an electric field from an external source that requires constant power. The active sensor produces an electrical pulse for each radioactive particle that collides with the sensor. These pulses must be continuously coefficiented to record the correct radiation dose. Power loss indicates that the dose is not measured. Active solid phase sensors are typically made from silicon and other semiconductors. Passive solid phase sensors use a medium charged with a device that maintains the electric field required to separate electron-hole pairs without drawing external power. Passive solid phase dosimeters often use so-called floating gates. Here, a gate is provided in the detection medium for electrical isolation. The floating gate is charged and provides an electric field for charge separation. See, for example, US Pat. No. 6,172,368 to Tarr. The medium on the floating gate is typically an insulator such as silicon oxide. However, it can also be a closed gas chamber. See U.S. Pat. No. 5,739,541 to Kahilainen. The passive solid phase electron detector provides a means of monitoring radiation compatible with the present invention.

Electronic dosimeters are battery powered and typically equipped with a digital display or other visual, auditory or vibration alarm function. These devices often provide the wearer with real-time dose rate information. For routine occupational radiation settings in the United States, electronic dosimeters are rarely used for access control, not for dose recording. Many cities and states provide the HAZMAT team with electronic dosimeters as part of their emergency response plan. Today, for example, tens of thousands of electronic dosimeters are installed for mainland safety purposes. However, due to its high cost, electronic dosimeters are not practical as general-purpose dosimeters.

Quartz or carbon fiber electrets are cylindrical electroscopes. Here, the dose is read by lifting the electret through the light and looking at the position of the fibers on the scale through the eyepiece at one end. A manual charger is needed to zero the dosimeter. Quartz fiber electrets are an important element of emergency plans in many states. For example, some plans require emergency responders to be provided with a quartz fiber electret, along with a card to record reads every 30 minutes, and a dose badge or wallet card to accumulate. While they are designated for use in emergencies in nuclear power plants, the NRC does not require them to be certified by NVLAP, but rather they simply need to be calibrated on a regular basis.

<p num="0014"> According to the first broad aspect, the present invention provides a device, which device is: One or more processors, and When run by the one or more processors, the one or more processors will take the following steps: (a) The step of determining the radiation dose value for the response matrix by determining the radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, A machine-readable medium for storing instructions, which performs operations including With Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of determining a radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0015"><maths num="1"><img id="000002" he="30" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0016"> (Here, i is the number of detector elements of the dosimeter, Where j is the number of irradiation fields, here,</p><p num="0017"><maths num="2"><img id="000003" he="21" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0018">Is the expected value of one or more dose conversion factors for the field j, here,</p><p num="0019"><maths num="3"><img id="000004" he="20" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0020">Is the computer-calculated dose for the i-th element and j-th irradiation field of the dosimeter, and Where σ_ijIs the total uncertainty of the stored response for the i-th detector element and j-th irradiation field of the dosimeter), and Each stored response is one of many stored responses stored in a second storage medium.</p><p num="0021"> According to the second broad aspect, the invention provides a machine-readable medium, which is one or more electronic devices when executed by one or more processors in the following steps: (a) The step of determining the radiation dose value for the response matrix by determining the radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, Contains a sequence of directives that perform a set of operations, including Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of determining a radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0022"><maths num="4"><img id="000005" he="35" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0023"> (Here, i is the number of detector elements of the dosimeter, Where j is the number of irradiation fields, here,</p><p num="0024"><maths num="5"><img id="000006" he="25" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0025">Is the expected value of one or more dose conversion factors for the field j, here,</p><p num="0026"><maths num="6"><img id="000007" he="22" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0027">Is the computer dose calculated for the i-th element and j-th irradiation field of the dosimeter, and Where σ_ijIs the total uncertainty of the stored response for the i-th detector element and j-th irradiation field of the dosimeter), and Each stored response is one of many stored responses stored in a second storage medium.</p><p num="0028"> According to the third broad aspect, the present invention provides a method, which is described in the following steps: (a) The step of determining the radiation dose value for the response matrix by determining the radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, Is a method, including Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of determining a radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0029"><maths num="7"><img id="000008" he="35" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0030"> (Here, i is the number of detector elements of the dosimeter, Where j is the number of irradiation fields, here,</p><p num="0031"><maths num="8"><img id="000009" he="22" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0032">Is the expected value of one or more dose conversion factors for the field j, here,</p><p num="0033"><maths num="9"><img id="000010" he="22" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0034">Is the computer-calculated dose for the i-th element and j-th irradiation field of the dosimeter, and Where σ_ijIs the total uncertainty of the stored response for the i-th detector element and j-th irradiation field of the dosimeter), and Each stored response is one of many stored responses stored in a second storage medium.</p><p num="0035"> According to the fourth broad aspect, the present invention provides a device, which device is: One or more processors, and When run by the one or more processors, the one or more processors will take the following steps: (a) The step of determining the radiation dose value for the response matrix by determining the radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, A machine-readable medium for storing instructions, which performs operations including With Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of determining a radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0036"><maths num="10"><img id="000011" he="21" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0037"> (Here, min is the minimized objective function, Where i is the number of detector elements in the dosimeter, Where j is the number of irradiation fields, Where cv_i^MEASIs the normalized measurement conversion value for the i-th detector element of the dosimeter, and Where cv_i^SOLUTIONIs the response for the i-th detector element of the dosimeter for the algorithmic solution region, and Each stored response is one of many stored responses stored in a second storage medium.</p><p num="0038"> According to a fifth broad aspect, the invention provides a machine-readable medium, which is one or more electronic devices when executed by one or more processors in the following steps: (a) The step of determining the radiation dose value for the response matrix by determining the radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, Contains a sequence of directives that perform a set of operations, including Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of determining a radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0039"><maths num="11"><img id="000012" he="24" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0040"> (Here, min is the minimized objective function, Where i is the number of detector elements in the dosimeter, Where j is the number of irradiation fields, Where cv_i^MEASIs the normalized measurement conversion value for the i-th detector element of the dosimeter, and Where cv_i^SOLUTIONIs the response for the i-th detector element of the dosimeter for the algorithmic solution region, and Each stored response is one of many stored responses stored in a second storage medium.</p><p num="0041"> According to the sixth broad aspect, the present invention provides a method, which is described in the following steps: (a) A step of measuring a radiation dose value for a response matrix by determining a radiation dose value for each field in the response matrix from many detector elements of the dosimeter. (b) Steps to determine the final net radiation dose value for each field in the response matrix, and (c) Display to the user the final net radiation dose value for each field in the response matrix and / or store the final net radiation value for each field in a first storage medium. Steps to do, Is a method, including Each irradiation field has a radiation source, Step (b) is the following step: (i) Steps that produce an initial solution vector for each field, (ii) The step of iteratively updating the initial solution vector for each field until the objective function is minimized, thereby producing the optimal solution vector, and (iii) A step of measuring the radiation dose value for each field based on the optimal solution vector for the source. Including steps to perform a numerical optimization process, including The objective function is</p><p num="0042"><maths num="12"><img id="000013" he="24" wi="134" file="JP6072943B2_D0001.tif" img-format="tif" img-content="drawing" /></maths></p><p num="0043"> (Here, min is the minimized objective function, Where i is the number of detector elements in the dosimeter, Where j is the number of irradiation fields, Where cv_i^MEASIs the normalized measurement conversion value for the i-th detector element of the dosimeter. Where cv_i^SOLUTIONIs the response for the i-th detector element of the dosimeter for the algorithm solution region. Each stored response is one of many stored responses stored in a second storage medium.</p>

<figref num="1">FIG. 1 schematically shows a device and computer computing process according to an exemplary embodiment of the present invention.</figref><figref num="2">FIG. 2 is a flowchart of a numerical optimization procedure according to one embodiment of the present invention.</figref>

The accompanying drawings are incorporated herein by reference and constitute a portion of the specification, illustrating exemplary embodiments of the invention, and the general description described above and the details below. It is useful to explain the features of the present invention together with the description.

(Definition) If a definition of a term deviates from the commonly used meaning of that term, Applicant intends to use the definition provided below unless otherwise indicated.

For the purposes of the present invention, "top", "bottom", "above", "below", "above", "below", "left", "right", "horizontal", "vertical" , "Upper", "downward", and other directional terms are used solely for convenience to describe various embodiments of the present invention.

For the purposes of the present invention, a value or property is "based on" a particular value or property by making a mathematical calculation or logical determination of that value using that value, property or other factor. Satisfy conditions or other factors when induced.

For the purposes of the present invention, the term "accelerometer" refers to an electromechanical device for measuring acceleration forces, including static or dynamic forces. Such acceleration is generally measured in terms of g-force. A single-axis or multi-axis model of an accelerometer is available to detect the magnitude and direction of the appropriate acceleration (or g-force) as a vector quantity, and the orientation (because the direction of weight changes). ), Coordinate acceleration (as long as it causes a change in g-force or g-force), vibration, impact, and resistance Can be used to detect drops in a medium (if the appropriate acceleration changes) , Because it starts from zero and then increases). MEMS scale accelerometers are increasingly present in portable electronic devices and video game controllers to detect the location of the device or provide game input. A pair of accelerometers that extend over a spatial area can be used to detect differences (gradients) in the appropriate acceleration of the frame of reference associated with those points. These devices are called gravitational gradient meters because they measure gradients in the gravitational field.

For the purposes of the present invention, the term "Bluetooth®" is used in the short range (2400-2480MHz ISM band) from fixed and mobile devices to create a personal area network (PAN) with a high level of security. Refers to the wireless technology standard for data exchange over (using short-wave radio broadcasting). When created in 1994 by telecom vendor Ericsson, it was first created as a wireless alternative to RS-232 data cables. It can connect several devices and solve the synchronization problem. Bluetooth® is managed by the Bluetooth® Special Interest Group and has more than 18,000 member companies in the areas of telegraph, computing, networking and consumer electronics. Bluetooth (registered trademark) is IEEE It was standardized as 802.15.1, but that standard is no longer maintained. The SIG oversees the development of specifications, manages accreditation programs, and protects trademarks. In order to be marketed as a Bluetooth® device, it must be certified to the standards set by the SIG. A network of patents is required to implement this technology and is licensed only for certified devices.

For the purposes of the present invention, the term "chemical sensor" refers to a device that measures the presence, concentration or absolute amount of a given chemical material, such as an element or molecule of either a gas phase, a liquid phase or a solid phase.

For the purposes of the present invention, the term "computer" refers to any type of computer or other device running software, such as personal computers, laptop computers, tablet computers, mainframe computers, minicomputers. Such as individual computers and the like are included. Computers are also electronic science equipment (eg servers, spectroscopes, smartphones, e-book readers, mobile phones, televisions, portable electronic game consoles, video game consoles, compressed audio or video players (eg MP3 players, Blu-ray players, etc.) Refers to electronic devices such as DVD players)). Further, the term "computer" refers to any type of computer network (eg, computer network in business, computer bank, cloud, internet, etc.). Various processes of the present invention can be performed using a computer. Various functions of the present invention may be performed by one or more computers.

For the purposes of the present invention, the term "computer hardware" is a physical device of a digital circuit and computer system, as opposed to computer software stored in a hardware device such as a hard disk.

For the purposes of the present invention, the term "computer network" refers to a group of interconnected computers. All networks consist of basic hardware building blocks that interconnect network nodes, such as network interface cards (NICs), bridges, hubs, switches and routers. In addition, some methods of connecting these building blocks are generally in the form of galvanized cables, optical cables (fiber optics), microwave links or other radio frequency transmissions (wireless network communications). Needed.

For the purposes of the present invention, the term "computer software" refers to a general term used to describe a set of documents that perform a task on a computer program, procedure, or computer system. The term refers to application software such as word processors that perform productive tasks for the user, system software such as operating systems that interface with hardware to provide the services required by the application software, and Includes middleware that controls and links distributed systems. Computer software is said to distinguish it from computer hardware, which includes physical interconnects and the devices needed to store, run (or run) the software. At the lowest level, the software consists of machine language specific to the individual processor. Machine language consists of a group of binary values that indicate processor instructions that change the state of a computer from its predecessor state.

For the purposes of the present invention, the term "computer system" is run by computer software on computer hardware such as supercomputers, mainframe computers, minicomputers, personal computers, embedded computers or other computing devices. Any type of computing system. Further, a computer system refers to any type of network of such computing systems.

For the purposes of the present invention, the term "data" means a reinterpretable representation of information in a formalized format suitable for communication, analysis or processing. One type of common type of data is a computer file, but the data can also be streaming data, web services, and so on. The term "data" is used to refer to data in one or more fragments.

For the purposes of the present invention, the term "database management system (DBMS)" refers to computer software designed for the purpose of managing databases based on various data models. A DBMS is a set of software programs that control the organization, storage, management, and retrieval of data in a database. DBMSs are categorized according to their data structure or type. It is a set of pre-written programs used to store, update, and retrieve databases.

For the purposes of the present invention, the term "database" or the term "data record" refers to a structured collection of records or data stored in a computer system. The structure is achieved by organizing the data according to the database model. The most commonly used model today is the relational model. Other models, such as hierarchical and network models, use a clearer representation of the relationship (see below for a description of the various database models). Computer databases rely on software to organize the storage of data. This software is known as a database management system (DBMS). Database management systems are categorized according to the database model they support. The model tends to determine the query language that allows access to the database. However, the large amount of internal engineering of the DBMS is independent of the data model and is associated with management factors such as performance, concurrency, integrity, and recovery from hardware failures. In these areas, there are significant differences between products.

For the purposes of the present invention, the term "detector element" refers to a dosimeter device used to detect a particular field of irradiation.

For the purposes of the present invention, the term "dose conversion factor" refers to an amount that is converted between an absorbed dose in the air and an individual dose equivalent, as determined by the reference laboratory.

For the purposes of the present invention, the term "dosimeter" refers to a device for measuring the exposure of an individual or object to radiation, particularly to a radiation source that can have a cumulative effect over a long period of time or over a lifetime. .. The present invention is summarized in a radiometer that measures exposure to ionizing radiation. Radiation meters are of fundamental importance in the fields of radiation measurement and health physics. Other types of dosimeters are acoustic dosimeters, UV dosimeters and electromagnetic dosimeters. Ionizing radiation such as X-rays, alpha rays, beta rays, and gamma rays cannot be detected by the human senses. Therefore, measuring devices such as dosimeters are used to detect, measure and record this, and in some cases an alarm sounds when a preset level is exceeded. The damage to the body of ionizing radiation accumulates and is related to the total dose received. Its SI unit is sievert. Therefore, radiation-exposed workers such as roentgen engineers, nuclear power plant workers, doctors using radiation therapy, laboratory workers using radionuclides and some HAZMAT teams wear dosimeters. Need to be attached to. As a result, their employers may keep a record of their exposure to ensure that they are below legal limits. Such a device may be recognized as a "legal dosimeter", meaning that it has been certified for use in recording personal doses for regulatory purposes.

For the purposes of the present invention, the term "energy compensating material" has gamma energy as compared to an ionizing radiation sensor exposed to no compensating material or filter material when placed between an ionizing radiation sensor and a source. Or any damping material whose response changes over a range of X-ray energy. Examples of energy compensating materials are plastic, aluminum, copper, tin, tungsten and the like.

For the purposes of the present invention, the term "error condition" refers to the result or determination of a dose calculation process that is disappointing and requires additional analysis to indicate anomalies or malfunctions in the dose calculation process. ..

For the purposes of the present invention, the term "expected dose from the field of irradiation" refers to the experimentally determined response of the detector to the reference field of irradiation.

For the purposes of the present invention, the term "hardware and / or software" refers to digital software, digital hardware, or a function that can be performed by a combination of digital software and digital hardware. Various features of the invention can be performed by hardware and / or software.

For the purposes of the present invention, the term "ionizing radiation" refers to radiation of energy high enough to cause ionization in the medium through which it passes. It can consist of high energy particle (eg, electrons, photons, alpha particles) currents or shortwave electromagnetic radiation (ultraviolet, X-ray, gamma). This type of radiation can cause damage to the molecular structure of a substance as a result of the direct transfer of energy to its atoms or molecules, or as a result of secondary electrons or particles emitted by the radiation. The present invention can be used to determine the dose of both direct and indirect ionizing radiation. When ionizing radiation is emitted or absorbed by an atom, it can liberate the atom's particles (typically electrons, protons, or neutrons, but sometimes the entire nucleus) from the atom. Such events can alter chemical bonds to form ions (usually in pairs), which are particularly chemically reactive. This greatly exacerbates the chemical and biological damage per unit energy of radiation. This is because the chemical bonds are broken in this process. It has many practical uses in medicine, research, construction and other areas, but poses a health hazard if used improperly. Exposure to ionizing radiation can cause damage to living tissue and can result in mutations, radiation diseases, cancer and death.

For the purposes of the present invention, the term "ionizing radiation sensor" refers to a device that measures the presence or activity of a material or substance that emits or produces ionizing radiation.

For the purposes of the present invention, the term "irradiation" refers to the conventional meaning of the term "irradiation", ie, from high energy particles (eg, electrons, protons, alpha particles, neutrons, etc.), or visible light. Also refers to exposure to short-wavelength electromagnetic radiation (eg, gamma rays, X-rays, ultraviolet rays, etc.).

For the purposes of the present invention, the term "laboratory-based dosimetry system" refers to the use of a central analytical laboratory for the disassembly, processing, and analysis of one or more components of a dosimeter. It refers to the required dosimeter analysis system.

For the purposes of the present invention, the term "low power wireless network" refers to an ultra-low power wireless network between a sensor node and a central device. Ultra-low power is required by devices that require operating energy scavenging technology from small batteries for extended periods of time. Examples of low power wireless networks are ANT, ANT +, Bluetooth Low Energy (BLE), ZigBee and Wi-Fi.

For the purposes of the present invention, the term "machine readable medium" can store, encode or possess instructions for execution by a machine, and the machine performs any one or more of the methods of the invention. Any tangible or non-transient medium capable of storing, encoding or retaining the data structures to be, or used by, or associated with such instructions. The term "machine readable medium" includes, but is not limited to, solid phase memory, as well as optical and magnetic media. Specific examples of machine-readable media include: Non-volatile memory (including, for example, semiconductor memory devices (eg, EPROM, EEPROM) and flash memory devices); magnetic disks (eg, internal hard disks and removable disks). Magnetic optical discs; as well as CD-ROM discs and DVD-ROM discs. The term "machine readable medium" may include a single or multiple medium (eg, a central or distributed database, and / or associated caches and servers) that stores one or more of the above instructions or data structures.

For the purposes of the present invention, the term "MEMS" refers to a microelectromechanical system. MEMS, in its most common form, refers to a technique that can be defined as an element (ie, device and structure) of a small mechanical and electronic machine made using microfabrication techniques. The critical physical dimensions of MEMS devices can range from well below 1 micron to a few millimeters at the bottom of the dimensional spectrum. Similarly, types of MEMS devices can range from relatively simple structures without moving elements to highly complex electromechanical systems with multiple moving elements under the control of integrated microelectronics. The main criteria for MEMS may be that there are at least some elements that have some sort of mechanical functionality as to whether these elements are movable or not. The terms used to define MEMS vary from region to world. In the United States they are primarily called MEMS, but in some other parts of the world they are "Microsystems". It is called "Technology" or "micromachined devices". Functional elements of MEMS are small structures, sensors, actuators, and microelectronics, but the most prominent elements can include microsensors and microactuators. Microsensors and microactuators can be appropriately classified as "transducers" and they are defined as devices that convert energy from one form to another. In the case of microsensors, the device typically converts the measured mechanical signal into an electrical signal.

For the purposes of the present invention, the term "optimized data fitting procedure" refers to the transformation of the parameters of a mathematical model for estimating the output response for a known set of input data. This procedure is optimal in the sense that it minimizes the error between known input data and the estimated output response.

For the purposes of the present invention, the term "processor" refers to a device that performs basic operations in a computer. A microprocessor is an example of a processor.

For the purposes of the present invention, the term "radiation attenuating material" refers to a material that attenuates the intensity of incident radiation by absorbing some or all of the energy of the radiation into the material.

For the purposes of the present invention, the term "individual dose equivalent" refers to a dose at a particular depth in a biological tissue for a particular field of irradiation. In one embodiment of the invention, the individual dose equivalent is H._p(10mm), H_p(0.07mm), and H_pIt means (3mm).

For the purposes of the present invention, the term "radiation metering" refers to the conventional meaning of the term "radiation metering", i.e., measuring the amount of radiation absorbed by the body of a material, object or individual.

For the purposes of the present invention, the term "radiation sensing material" refers to a material used to sense radiation in a radiation sensor. Examples of radiation sensitive materials include photoexcited luminescence materials for OSL sensors, thermoluminescent materials for thermoluminescent dosimetry (TLD) sensors, and the like.

For the purposes of the present invention, the term "real-time processing" refers to a processing system designed to process a workload whose state is constantly changing. Real-time processing means that a transaction is processed fast enough for the results to be returned and acted upon when a transactional event occurs. In the context of a database, a real-time database is a database that can produce a reliable response in real time.

For the purposes of the present invention, the terms "radioactive source" and the term "radioactive source" are used interchangeably to refer to radiation sources such as X-rays, gamma rays, alpha particles, beta particles and neutrons. Each radiation source has one or more related fields of radiation.

For the purposes of the present invention, the term "sensor" refers to a collector and / or producer of information and / or data. The sensor can be a device or a living organism (eg, a human). For example, the sensor can be a GPS device, a thermometer, a mobile phone, an individual writing a report, and so on. A sensor is an entity that can observe a phenomenon and return the observed value. For example, a mercury thermometer converts a measured temperature into a stretch of liquid, which can be read on a graduated glass tube. The thermocouple converts the temperature into an output voltage, which can be read by a voltmeter. For accuracy, all sensors are often calibrated to known standards. A sensor may include a device that detects or measures a physical property and records, displays, or responds to that physical property.

For the purposes of the present invention, the term "solid phase sensor" refers to a sensor entirely constructed from solid phase material. Thereby, contrary to gas exchange or electromechanical sensors, the electrons or other charge carriers generated in response to the measured amount remain entirely in the actual volume of the detector. A pure solid phase sensor has no moving parts and is different from an electromechanical transducer or actuator whose mechanical motion occurs in proportion to the measured amount.

For the purposes of the present invention, the term "solid phase electronics" is a circuit or device entirely constructed from a solid material, in which electrons or other charge carriers are totally confined. It means what is. The term is often used to contrast with the technology of early tube and gas discharge tube devices, and it is also conventional, from the term solid phase to electromechanical devices (relays, switches, hard drives, and moving parts). Other devices that have) are excluded. Solids can include crystalline, polycrystalline, and amorphous solids, and can be conductors, insulators, and semiconductors, but the construction material is most often crystalline semiconductors. Common solid phase devices include transistors, microprocessor chips, and RAM. A special type of RAM, called flash RAM, is used in flash drives and, more recently, in solid phase drives to replace mechanically rotating magnetic disk hard drives. More recently, integrated circuits (ICs), light emitting diodes (LEDs), and liquid crystal displays (LCDs) have evolved as further examples of solid phase devices. In solid phase components, current is confined to solid elements and compounds specifically designed for their switching and amplification.

For the purposes of the present invention, the term "storage medium" or "storage device" refers to any tangible medium in which data and / or instructions may be stored for use by a computer system. Examples of data storage media include floppy disks, CD-ROMs, CD-Rs, CD-RWs, DVDs, DVD-Rs, memory sticks, flash memories, hard disks, solid disk disks, optical disks, and the like. Two or more data storage media that act like a single data storage medium may be referred to as "storage media" for the purposes of the present invention.

For the purposes of the present invention, the term "stored response" refers to the stored response of a detector element to a known field of irradiation. Known fields of irradiation can be from a single pure source and / or a mixture of sources. Uncertainty can be associated with the stored response.

For the purposes of the present invention, the term "time" is a measurement system used to arrange events, compare the length of events and the intervals between them, and quantify the motion of an object. Refers to the components of. Time is considered one of the few basic quantities and is used to define quantities such as velocity. Operational definition of time (where, observation of a certain number of iterations of one or another standard circular event (such as the passage of a freely swinging pendulum) is one standard unit (eg, second). Has high utility value in both advanced experimental and daily activities. Temporal measurement attracted scientists and engineers and was the number one motivation in navigation and astronomy. Periodic events and motions have long served as the standard for units of time. Examples include the apparent movement of the sun across the sky, the phase of the moon, the swing of the pendulum, and the beating of the heart. Currently, the international unit of time, seconds, is defined based on the radiation emitted by the cesium atom.

For the purposes of the present invention, the term "timestamp" refers to a character array indicating the date and / or time at which a particular event occurred. This data is usually presented in a consistent format, allowing easy comparison of two different records and tracking progress over time; the act of recording time stamps in a consistent format with real data is time stamping. Is called. Typically, a time stamp is used to record the event, in which case each event in the log is time stamped. In a file system, a time stamp can mean the storage date / time of a file's creation or modification. The International Organization for Standardization (ISO) defines ISO 8601 and standardizes time stamps.

For the purposes of the present invention, the term "visual display device" or "visual display device" refers to a printer for printing out images such as CRT monitors, LCD screens, LEDs, projector displays, photographs and / or text. Refers to any type of visual display device or device such as. Visual display devices include computer monitors, televisions, projectors, phones, mobile phones, smartphones, laptop computers, tablet computers, portable music and / or video players, personal information terminals (PDAs), portable game players, head-mounted displays. , Head-up display (HUD), Global Positioning System (GPS) receiver, automatic navigation system, dashboard, watch, microwave oven, electronic organ, part of another device such as automatic cash depository (ATM) It may be.

For the purposes of the present invention, the term "weighting factor" refers to the contribution of each field to the estimated output response.

For the purposes of the present invention, the term "ZigBee" refers to a specification for a set of high-level communication protocols used to create a personal area network constructed from small low-power digital radios. ZigBee is IEEE Based on the 802 standard. Low-power ZigBee devices often transmit data over longer distances by passing data through intermediate devices to reach more distant ones, reaching mesh networks: that is, all networked devices. Create a network without centralized control or high power transmitter / receiver. The decentralization of such wireless ad hoc networks makes them suitable for applications where the central node is unreliable. ZigBee can be used in applications that require low data speeds, long battery life, and secure networking. ZigBee has a defined speed of 250 kbit / s, which is ideal for the transmission of periodic or intermittent data or a single signal from a sensor or input device. Applications include wireless light switches, electric meters with home displays, traffic management systems, and other consumer and industrial equipment that require short-range wireless transmission of data at relatively low speeds. The technology specified by the ZigBee specification is intended to be simpler and cheaper than other WPANs (eg Bluetooth® or Wi-Fi). The Zigbee network is protected by a 128-bit encryption key.

(Description) Existing passive integrated radiation monitoring devices (eg, film, TLD or OSL sensors) do not require any power and the incident radiation is stored and stored within the crystal structure of the sensor. This property makes passive sensors ideal for situations where the risk of power failure is unacceptable. Generally, a plurality of radiation sensors are installed in a holder containing one or more filters. This filter changes the amount, energy and type of radiation that can reach the sensor. Typically, these filters sandwich the sensor so that radiation can get an accurate assessment as it enters the dosimeter from various angles of incidence. To analyze the sensors, they are removed from between these filters and holders and physically into the processing system required to elicit the quantitative properties exhibited by the sensor after exposure to radiation. Must be presented.

Optically stimulated luminescence (OSL) -based radiometers use an optical path so that excited rays can illuminate the OSL sensor (s), and the resulting radiation-induced luminescence can be the same or an alternative path. It passes through and returns to a photodetector (eg, a photoelectron multiplier) to quantify the amount of luminescence light.

The individual dose equivalent measured using a radiometer is the most commonly used metric of radiation dose to an individual. Accurate and reliable measurement of personal dose equivalent is a key element of radiation dose measurement. Personal dose equivalents are typically measured from a variety of radiation sources, including X-rays, gamma rays, alpha particles, beta particles and neutrons, over a wide range of energies. To accurately estimate doses from different sources, many personal dosimeters incorporate an array of detector elements, each of which has a different type of radiation filtration material, and the response from each detector element. A dose calculation algorithm is used to accurately calculate the individual dose equivalent from the numerical combination.

In one embodiment, the present invention provides a small, low cost, self-contained field readable radiation meter. This dosimeter provides accurate calculations of personal dose equivalents over a wide dose range, a wide energy range, and over large angles of incidence.

In one embodiment, the invention provides a procedure for calculating an appropriate absorbed radiation dose value from a detector system. The detector system can be a number of sensor devices (eg, two or more integrated ionizing radiation sensors, MEMS scale accelerometers, geospatial positioning sensors (eg GPS), thermistas, energy harvesters, or chemistry, biology, Can include ultraviolet (UV) or Electromagnetic Frequency (EMF) sensors).

In one embodiment, the invention results in reading measurements from a sensor from an instrument or storage medium, converting raw input sensor data into the required dose information, and for use in occupational and environmental dosimetry. Includes output transmission and storage. In one embodiment, the invention uses accurate data adaptation optimizations for dosimeters tailored to a particular application and is easy to update without modification to the underlying software program. Computer-calculable on embedded firmware and requires two or more sensor elements, including passive and active dosimeters, and field-readable portable dosimeters Provide methods that are compatible with any dosimeter system, as well as laboratory-based dosimeter systems.

Radiation attenuating materials are used to modify the response of non-tissue equivalent radiation sensors to allow a variety of responses to a wide range of radiation qualities. The modified response can then be used by an algorithm to derive tissue equivalent dose. By using multiple damping materials around multiple sensors with the use of the Softway algorithm, it is possible to increase the level of fine discrimination between the types of ionizing radiation and radiation energy.

A further advantage of the embodiment of the description of the multi-sensor output using the time, operation, location and direction of the dosimeter at the point of exposure is that the dosimeter can be used during the time of exposure, the location of exposure, and the event of exposure. It further allows the determination of whether it was worn (and correctly). Knowing that the dosimeters were properly fitted at the time of the exposure is important to characterize the nature of the exposure, the effectiveness of the calculated doses, and the potential risk to participants. In addition, knowing the time of the bombing is important for reconstructing pre-exposure events and can help characterize the duration, source, and nature of the bombing. Rapid access to this information is an important element of radiation safety and radiation measurement programs. Directional detection allows correction of dose calculations for fluctuations based on incident angle and source direction. Temperature detection allows correction of dose calculations for temperature-based fluctuations.

Accurate and reliable measurements of individual dose equivalents are a key component of radiation dose programs. Personal dose equivalents are typically measured over a wide range of energies and from different sources of radiation, including, for example, X-rays and gamma photons, beta particles and neutrons. To accurately estimate doses from different radiation sources, personal dosimeters incorporate multiple detector elements, each with different types of radiation filtration material, and use a dose calculation algorithm for each detector. Calculate the personal dose equivalent from a numerical combination of responses from the elements.

One approach for calculating dose is to use a simple linear combination of detector element responses. While such an approach is straightforward and easy to implement, it is very sensitive to noise and often does not provide reliable estimates of dose under realistic conditions. Another approach is to use empirically determined branches and decision points. According to an exemplary embodiment of the invention, this approach is relatively easy to implement and improves performance under some conditions, but empirical decisions are specific to certain conditions. And often susceptible to systematic bias. Techniques for applying both linear combinations and bifurcation methods for radiation measurements include, for example, N. Stanford (eg, N. Stanford, Whole Body Dose Algorithm for the Landauer InLight Next Generation Dosimeter, Algorithm Revision: Next. Gen IEC; Sept. 13, 2010 and N. Stanford, Whole Body Dose Algorithm for the Landauer InLight Next Generation Dosimeter, Algorithm Revision: Next Gen NVLAP; Sept. 27, 2010 and N. Stanford, Linear vs. Functional-Based Dose Algorithm Designs, Rad. Prot. Dosim., Developed by 144 (1-4), 253-256 (2011)).

In one embodiment, the invention automates a dose calculation algorithm that is numerically optimized for a particular dosimeter type (ie, a particular combination with a dosimeter detector element, filter and other sensor elements). A computer calculation procedure for generating an algorithm is provided. To minimize systematic deviations, the computerized procedures of the disclosed embodiments calculate a weighted average from representative data, and the resulting dose is a given field, detector, or Overall, it does not depend on the ratio of detector signals. The following describes the computer calculation procedure used to generate a numerically optimized dose calculation algorithm for a personal dosimeter using a matrix of element responses obtained from measurements of that dosimeter type.

For example, when using a personal dosimeter consisting of detector elements or sensors with multiple filters, the signal detected from each detector element is called the element response, and an array of element responses from a given dosimeter. Is called the element response pattern of the detector. For a given dosimeter type, the matrix resulting from multiple detector element responses at different but known irradiations is referred to as the element "response matrix" or simply the "response matrix".

The response matrix is made by exposing the dosimeter to known irradiation at different angles and to a mixture of individual or multiple sources, and then reading the element response from each detector element. The element response pattern from the unknown irradiation dosimeter is then compared to the pattern in the element response matrix, and the dose is calculated for each irradiation field in the response matrix. The final reported dose is the sum of all individual source doses weighted by the Source Probability Factor. The source probability factor is a measure of how closely the element response patterns of an unknown dosimeter fit into the individual element response patterns of a known source.

FIG. 1 shows a computer 102 including a processor 104 for performing process 106 to produce a numerically optimized radiation dose calculation for a personal dosimeter according to one embodiment of the invention. When process 106 is started in step 110, raw data 112 (consisting of measured dosimeter signals, background dose information, and response matrix) is read from the dosimeter 114. The raw data 112 is then stored in storage media, i.e., memory 116 of computer 102, which can be, for example, computer memory or a hard drive, and formatted for the processing of step 118. Alternatively, the raw data 112 previously stored in memory 116 before process 106 begins may be formatted for further processing in step 118. The term "formatted for processing" in this context means moving data from computer memory or disk and inserting it into a data structure containing dosimeter signal, background dose, and response matrix values. To say.

Reading the raw data 112 from the dosimeter 114 can be via an offline (external) reader or via real-time wired or wireless communication between the dosimeter 114 and the computer 102. This can be done in a number of ways, including using an external reader to record the dosimeter signals from each of the multiple detector elements, or electrically connecting the computer 102 to the dosimeter 114. By wireless communication between the dosimeter 114 and the computer 102; or by storing the raw data 112 in an external storage device (eg, a memory stick) inserted in the dosimeter 114 and storing the stored raw data. By inserting the device into computer 102. For dosimeters that use optically stimulated luminescence (OSL) (eg, LANDAUER's InLight® dosimeter), the dosimeter element response corresponds to the coefficients from the InLight® reader's photomultiplier tube (PMT). To do.

Memory 116 (a machine-readable medium) stores a sequence of commands. This sequence of directives is processor 104 when executed, because one or more electronic devices execute process 106. Process 106 processes the raw data 112 (eg, dosimeter readings, background dose, and response matrix) and converts the raw data 112 into useful information. This information may also be written to memory 116, and this information may be displayed to the user as needed.

At step 120, the error condition is checked by computer 102 and if detected, error 122 can be flagged at step 120 and all errors can be tracked / listed on memory 116. If there are no errors in step 124, the raw data 112 read from the dosimeter 114 is processed by computer 102 in step 126 to normalize the dosimeter signal and response matrix of the raw data 112. At step 128, a numerical optimization procedure is called by computer 102 to match each unknown signal pattern in the raw data to a known signal pattern in the response matrix. At step 130, computer 102 applies the appropriate dose conversion factor to the dose contribution of raw data 112 for each field. In step 132, the reportable dose is calculated by computer 102 by summing the weighted dose contributions for each field output dose. The quality is evaluated in step 138 by summing over this weighting factor multiplied by the source energy and particle identification.

At step 134, if an error condition is checked and detected on computer 102, error 136 can be flagged at step 134 and all errors can be tracked / listed in memory on memory 116. If no error is detected by computer 102, then in step 138, the radiation quality is evaluated using the source weighting factor and the output dose. Based on the result of step 138, the quality information 140 is stored in the memory 116. In step 142, the net dose 144 is calculated by computer 102 by subtracting the reportable dose and background dose. The calculated net dose 144 is stored in memory 116 by computer 102. At step 146, the computer 102 determines whether the data stored in memory 116 needs to be reviewed. The calculated dose data may need to be reviewed in the event of one or more error conditions. If the computer 102 determines in step 146 that the data stored on the storage medium needs to be reviewed, then a query is made from the read raw data for the data on quality and the calculated dose. The data is stored in memory and the results are displayed to the user on the visual display device 150. If computer 102 determines that the data review is complete in step 152, then computer 102 creates a report in step 154. Process 106 ends at step 156 after the report was created at step 154. If the data review is not complete, step 148 is performed on computer 102 for a new query. The review of the data will not be completed unless the original error condition is resolved, in which case the dose will be recorded as invalid. If it is determined in step 146 that the data does not need to be reviewed, process 106 ends at 156.

For simplicity, FIG. 1 shows a single processor, but the processors of the present invention may include one or more processors.

In one embodiment of the invention, in step 118, the dosimeter element response and the corresponding dosimeter response matrix for that type of dosimeter are populated, and then the conversion value is calculated. For dosimeters that use optically stimulated luminescence (OSL) (eg, LANDAUER's InLight® dosimeter), the dosimeter element response corresponds to the coefficient from the InLight® reader's photomultiplier tube (PMT). To do. The conversion value is calculated from the PMT coefficient as shown in Equation 1 below:

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In one embodiment of the invention, the normalization process of step 126 comprises applying a mathematical algorithm that uses a defined numerical procedure to optimize the response matrix. This may include calculating the expected source dose using an optimized data matching procedure. The inputs are the converted value, the sensor output, and the source response. The response matrix weighting factor can be calculated using a goodness-of-fit statistical test. The weighting factor indicates how much each field contributes to the final net dose.

In one embodiment of the invention, step 126 uses a chi-squared minimizer goodness-of-fit to calculate the response matrix weighting factor. This is computer computationally efficient, but cannot converge to a globally optimal solution if there are multiple minimums. Numerous discovery search algorithms have been developed to automatically find global optimums. These include simulated annealing, listing, exploration, and genetic algorithms. Genetic algorithms have been shown to overcome many of the traditional minimizer limitations in complex numerical optimization problems (see: Yuan Xu; Scott Neu; Chester J. Ornes; Janis F. . Owens; Jack Sklansky; Daniel J. Valentino; Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms. Proc. SPIE 4684, Medical Imaging 2002: Image Processing, 1406, May 15, 2002; doi: 10.1117 / 12.467106). Each computer computing technique has its own advantages and limitations. The design of the algorithm can be adapted to include any of the commonly used optimization techniques without adversely affecting the performance of the algorithm.

In one embodiment of the invention, in step 128, the response matrix selection may be based on empirically guided rules. For example, the range of sources in the response matrix can be limited based on empirically derived decision points in order to achieve optimal performance for a particular application.

In one embodiment of the invention (when raw data is read from LANDAUER's InLight® dosimeter), the response matrix is source, individual element response, H._p(0.07 mm) or surface dose equivalent (SDE) conversion factor, H_p(10 mm) or deep dose equivalent (DDE) conversion factor, H_pIncludes an entry (variable) that describes the (3 mm) or lens dose equivalent (LDE) conversion factor, radiation type, radiation energy, and standard deviation of the response. In this embodiment of the invention, in step 130, the computer 102 applies an appropriate dose conversion factor to the dose contribution of the raw data 112 of each irradiation field measured by the dosimeter 114. In this embodiment of the invention, the appropriate dose contributions are the weighting factor, the expected source dose, and the individual dose equivalent (eg, H respectively)._p(10mm), H_p(0.07mm), H_pIt can be calculated from the product of the dose conversion factors for (3mm)).

In one embodiment of the invention, steps 132, 138 and 142 can be performed by computer 102 as follows: Based on a set of measurement conversions, the individual doses (G1 to G4) for each field are calculated in step 132. At step 138, each of these individual doses is given a weighted value based on the matching parameters. At step 142, the weighted values of the individual doses are summed to obtain the average calculated dose. Values G1 through G4 for a given field of irradiation are H if this given field of radiation exactly matches the actual field of incidence seen by the dosimeter._pIt indicates what the (0.07 mm) or surface dose equivalent (SDE) is. Converting the element response to G1 through G4 in this way yields a response matrix and measured conversions with the same scale. In this way, the conversion values and response matrix can be compared numerically.

FIG. 2 shows further details of the numerical optimization step 202, which is called in step 128 of process 106 and performed by computer 102. When called in step 128 of process 106, numerical optimization step 202 begins in step 212 to read the dose meter raw data 112 and initialize the response matrix noise 214. At step 216, for each irradiation field, the solution vector 218 is initialized and written to storage memory 116, which can be, for example, computer memory or a hard drive. At step 220, the objective function is initialized and written to memory 116. At step 222, it is determined whether the solution vector 218 has converged or the maximum iteration count for the numerical optimization procedure 202 has been reached.

If it is determined in step 222 that the solution vector 218 has not converged and has not reached the maximum number of iterations to generate the solution vector, then in step 224 a new solution vector 218 arises. Then, in step 226, the objective function is recalculated. At step 228, computer 102 determines whether this new solution vector minimizes the objective function . If this new solution vector does not minimize the objective function, in step 222 the computer determines whether the new solution vector has converged or reached the maximum number of iterations. If this new solution vector minimizes the objective function, the solution vector is updated to memory 116 in step 230 and this new solution vector becomes the "optimal solution vector" used to calculate the dose contribution. ..

In step 222, if it is determined that the solution vector 218 has converged or the maximum number of iterations to generate the solution vector has been reached, in step 232 the computer 102 has converged the noise stimulus or about sampling noise. Determine if the maximum number of iterations has been reached. In step 232, if computer 102 determines that this noise stimulus did not converge and did not reach the maximum number of iterations, then in step 234 computer 102 samples the noise and applies the noise to the response data. .. Then, in step 216, the solution vector is initialized and written to memory 116 based on the correction response data stored in memory in step 234.

If computer 102 determines in step 232 that the noise stimulus has converged or has reached the maximum number of iterations, computer 102 solves in memory 116 in step 236 to produce a weighting factor and dose contribution 238. Calculate the dose from the vector. Then, at step 240, the numerical optimization step 202 ends and the rest of process 106 resumes at step 130.

Specific details of the steps of process 106 and the numerical optimization procedure 202 according to the various embodiments of the present invention are described below.

In process 106, H for a given field_pThe expected value of (0.07 mm) could be considered as a simple average of the element dose values. However, this can be inadequate due to the fact that for some incident fields, some detectors can have signals with a high level of uncertainty. This would be true for the dosimeter response to low energy beta particles (eg, krypton-85 beta particles) incident on a detector with filtration at a density thickness of 0.1 g / cc. The radiation-induced signal received from the filtered element is too low relative to the measured noise level to adequately distinguish the radiation signal with a low level of uncertainty.

Therefore, in one embodiment of the invention, the signal of each detector is to ensure that the radiation dose for an individual, room, region, etc. is calculated only with a detector that has a good signal. Is weighted by a coefficient that is inversely proportional to the expected uncertainty, and a weighted average is performed across the detector. The first set is to define the expected uncertainty. Assume that each response matrix entry is determined from data to which the coefficient statistics are negligible (high dose). This error is a combination of irradiation, reading, handling, and uncertainty due to material variables. This combinatorial error is computer-calculated as the standard deviation of the data used to generate the response matrix, which is symbolized by σ.

In one embodiment of the invention, in step 126 of process 106, the signal for a given detector can be multiplied by zero if the measured conversion value for that detector is below a certain level. In this embodiment, no detector is used that is set to zero in any further computation, thereby reducing the dimensions of the dataset and improving computer computation efficiency.

In one embodiment of the invention, H for field j_p(0.07mm), H_p(10mm), H_pThe expected value of (3mm) is

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(See Equation 2 below) and used as the dose conversion factor in step 103 of process 106 in FIG. G_ijIs the computer-calculated dose for the i-th element and j-th irradiation field of the detector. The total uncertainty of the response stored for the i-th detector element and the j-th irradiation field is σ._ijSymbolized by.

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In this embodiment of the invention, the uncertainty of the stored response is explained and the effect of measured noise on the calculated dose is minimized. This is an improvement over traditional dose calculation algorithms that do not directly use uncertainty in dose calculation.

Uncertainty values used by algorithms for dose computer calculations can be randomly sampled using stored uncertainty values in the probability distribution and response matrix. This is known as noise sampling. The dose calculation can be performed several times with different noise samples for a single dosimeter, as shown in steps 232 and 234 of the numerical optimization procedure 202. Thereby, the dose distribution can be estimated, which can be used to further improve the accuracy of the reported dose.

In one embodiment of the invention, the objective function used in the number optimization procedure 202 is χ.²Similar to the coefficient of fit goodness-of-fit statistic, and called the chi-square optimization process. The chi-square optimization objective function for the single irradiation field j is expressed by Equation 3.

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In the chi-square optimization process, the set of weighting factors is used to determine the contribution of each field in the response matrix to the final reportable dose. The weighting factor for region j is calculated using Equation 4 below. The set of weighting factors associated with each field in the response matrix is a solution vector such as the solution vector 218 shown in process 106. The format of the solution vector is expressed by Equation 5 below.

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Once the weighting factors have been calculated for each region in the response matrix, the report SDE value G_repIs calculated. This is each irradiation field across the entire response matrix

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This can be done by taking the weighted sum of the expected values for (see step 132). This is expressed by Equation 6 below, where the sum is done over the N-region response matrix.

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A quantification of the approximation between the response pattern of the measured set of conversions and the region in the response matrix can be derived using many optimization techniques. In one embodiment of the invention, χ²Functions that approximate the statistics can be used as shown in Equations 3 and 4. The source specific statistical weighting factor is an empirical measure of how a set of measurement conversion patterns fits well with the patterns found in the response matrix.

In one embodiment of the invention, the solution vector can be defined as a set of weights that minimizes the objective function. Another definition of the objective function is given in Equation 7 below. Numeric optimizers typically follow a routine that is iteratively updated until an initial solution vector is generated and the objective function is minimized. In equation 7, cv_iIs the normalized conversion value, and the superscript represents the measurement conversion value and the stored response for the i-th detector element.

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In step 134 of process 106, the error condition is checked. In this step, common error conditions are checked, and if detected, the appropriate error conditions are set. If a serious error condition is detected, the error condition indicates that the calculated dose was not valid. If no serious error occurs, the calculated dose is considered valid.

In step 148 of process 106, the most promising source of radiation is estimated. In this step, the possible contribution of each field in the response matrix is calculated. In the current embodiment of the algorithm, the possible contributions of photons and beta particles and their effective energies are estimated. This information is used to assess the type of field of irradiation (eg, pure or mixed fields of radiation) and the energy of the radiation. A pure field of radiation is radiation originating from a single source (eg, a single radioisotope). A mixed field of radiation is radiation from various radioisotopes.

In step 142, the final (net) dose value is calculated. In this step, the net dose is calculated by subtracting the control dose from the already calculated dose. Only net doses greater than the minimum detectable dose are reported (a common practice is to report positive dose values; negative doses are backgrounds in which the relevant dose is predicted. Indicates that it was less than the ground dose, but it is not generally reported).

In step 154, the net dose value is output, for example, from memory to the storage device. In this step, the net dose is assigned to a particular dosimeter using the unique identification values stored in the dosimeter information database. The calculated net dose in computer memory is stored in the database (or exported to an external data file as needed). The results can be formatted and allow the generation of dose-of-record customer dose reports as required by regional, national or international regulations.

In various embodiments, the present invention provides computer computing procedures that result in numerically optimized dose calculation algorithms. The resulting computer calculation procedure dose algorithm is a personal dose equivalent for a personal dosimeter (eg H)._p(10mm), H_p(3mm) and H_p(0.07mm)) provides accurate and reliable measurements while avoiding systematic errors introduced by other technologies. Some of the advantages of the disclosed computer computing procedures include the ability to generate numerically optimized algorithms, the lack of branching or empirical decision points, and fast computational speed. The disclosed computer calculation procedures are also easily optimized for dosimeter design, regulatory standards, or the user's irradiation environment. Therefore, the dosimeter system using the algorithm resulting from the calculation procedure of the disclosure and the embodiments of the present disclosure have achieved compliance with the requirements of NVLAP and IEC 62387.

The devices and subsystems of the disclosed exemplary embodiments may store information related to the various processes described herein. This information may be stored in one or more memories of the devices and subsystems of the disclosed exemplary embodiments (eg, hard disks, optical disks, magneto-optical disks, RAM, etc.). A database of one or more of the device good subsystems of the invention may store information used to perform the various processes of the invention. Databases are organized using data structures (eg, records, tables, arrays, fields, graphs, trees, lists, etc.) contained in one or more of the memory or storage devices listed herein. obtain. The processes described for the disclosed exemplary embodiments store the data collected and / or generated by the processes of the devices and subsystems of that embodiment in the database of one or more of the disclosed exemplary embodiments. It may contain a suitable data structure to do so.

All or part of the devices and subsystems of the various embodiments of the invention are one programmed according to the teachings of the exemplary embodiments of the invention, as understood by those skilled in the art of computers and software. It can be conveniently performed using a general purpose computer system, a microprocessor, a digital signal processor, a microcontroller, or the like. Suitable software can be readily produced by a programmer with conventional skills based on the teachings of the exemplary embodiments, as will be appreciated by those skilled in the art of software. In addition, the devices and subsystems of the disclosed exemplary embodiments will be understood by those skilled in the art of electricity, by making application-specific integrated circuits, or by interconnecting suitable networks of conventional components. Can be done by Thus, the exemplary embodiments are not limited to any particular combination of hardware electrical circuit configurations and / or software.

When stored in any one or combination of computer-readable media, the exemplary embodiments of the invention are for controlling the devices and subsystems of the disclosed exemplary embodiments; the devices of the disclosed exemplary embodiments. And to drive subsystems; to interact with the device and subsystem of the disclosed exemplary embodiments with a person who is a user; and so on. Such software may include, but is not limited to, device drivers, firmware, operating systems, development tools, application software, and the like. Such a computer-readable medium further performs the computer program of the embodiment of the present invention in order to perform all or part of the processing performed in performing the disclosed exemplary embodiment (if the processing is distributed). Can include products. The computer code device of an exemplary embodiment of the invention may include, but is not limited to, a script, an interpretable program, a dynamic link library (DLL), which may include any suitable interpretable or executable code mechanism. Examples include Java classes and applets, full executable programs, and more. In addition, some of the processing of the exemplary embodiments of the invention may be distributed for better performance, reliability, cost, and the like.

As mentioned above, the devices and subsystems of the disclosed exemplary embodiments retain instructions programmed according to the teachings of the present invention, and the data structures, tables, records and / as described herein. Alternatively, it may include a computer-readable storage medium or memory for holding other data. The computer-readable medium may include any suitable medium involved in providing instructions to the processor for execution. Such media can take many forms and include, but are not limited to, non-volatile media, volatile media, communication media and the like. Examples of the non-volatile medium may include an optical or magnetic disk, a magneto-optical disk, and the like. Examples of the volatile medium include dynamic memory. Examples of the communication medium may include a coaxial cable, a copper wire, an optical fiber, and the like. The communication medium may also take the form of sound waves, light waves, electromagnetic waves, etc. (eg, those generated between radio frequency (RF) communication, infrared (IR) data communication, etc.). Common form of computer-readable medium For example, floppy disks, flexible disks, hard disks, magnetic tapes, any other suitable magnetic medium, CD-ROM, CDRW, DVD, any other suitable optical medium, punched cards, paper tape, optics. Any other suitable physical medium with a mark sheet, hole or other optically recognizable mark pattern, RAM, PROM, EPROM, FLASH-EPROM, any other suitable memory chip or cartridge, carrier, or Any other suitable medium that can be read by a computer can be mentioned.

In one embodiment, the invention collects data from Valentino et al., Filed on May 31, 2013, "WIRELESS, MOTION AND POSITION-SENSING, Processed and re-processed by computer as described and shown in U.S. Patent Application No. 13 / 906,553 entitled "INTEGRATING RADIATION SENSOR FOR OCCUPATIONAL AND ENVIRONMENTAL DOSIMETRY" (the entire content and disclosure of which is incorporated herein by reference). Central location for distribution Extends the possibilities and uses of traditional stand-alone dosimeters by allowing them to be sent to location). In such an embodiment, the computer-read dosimeter can be an integrated sensor module integrated into a dosimetry badge. The dosimetry badge can be a package and includes, for example, a disclosed electronic packaging with an integrated sensor module, battery and cover. The integrated sensor module collects radiation data and data to a remote location (eg, a wireless base station) or other wireless communication device (eg, a mobile communication device with a processor to process raw data from a dosimeter). Is finally sent. The remote sensor chip of the integrated sensor module can be used to transmit data. In this case, the data may be transmitted via a wireless transmission communication protocol (eg, Bluetooth®, Bluetooth Low Energy (BLE), ZigBee, ANT, ANT + or other standard Wi-Fi protocol).

The mobile communication device, including the processor for processing the raw data, can be a smartphone, tablet or mobile hotspot, or it can be a non-mobile network device such as a dedicated base station. Mobile communication devices can be configured to include wireless transmitters, data network interfaces and Global Positioning System (GPS). The dosimeter integrated sensor module may include a wireless system on chip (SOC) module configured to communicate with a wireless transmitter. The wireless transmitter can be a low power wireless network interface for mobile communication devices. The network interface allows the mobile communication device to communicate with the integrated modular wireless sensor chip to download the collected data. The communication facilitates the determination of whether the mobile communication device is within range of the integrated sensor module.

Mobile communication devices can also be configured to include a data network interface. A data network interface allows a mobile communication device to communicate with another wide area wireless network, for example via a data network transmission communication protocol. Suitable data network transmission communication protocols include Wi-Fi, GSM / EDGE, CDMA, UTMS / HSPA +, LTE and other high speed wireless data communication networks. In one embodiment of the invention, Bluetooth® is used between a dosimeter or dosimetry badge and a mobile communication device (eg, wireless) to process raw data from the dosimeter or dosimetry badge. It can be used to communicate (via a transmission communication protocol), and communicate between a mobile communication device and a wireless network in a remote facility such as a hospital or laboratory (eg, via a data transmission communication protocol). For LTE (Long-Term) Evolution) can be used. For example, by communicating over a public data network, the remote facility (eg, a hospital or laboratory) may reach, access, and / or process information deposited on a distributed data server.

Dosimeters may include GPS, which allows mobile communication devices to locate radiological events. GPS radio, a mobile communication device, provides an alternative means of locating integrated sensor modules. When the integrated sensor module is paired with a mobile communication device, the mobile communication device may preferentially use the GPS sensor to determine the location to minimize its own power consumption.

Wireless networks can be configured to communicate with public data networks (eg, the Internet). A remote data server equipped with a processor that processes raw data from a dosimeter may be configured to communicate with a public data network (eg, the Internet).

Using an electronic data transmission link formed between the mobile communication device and the remote data server, the integrated sensor module can transfer the measured raw data to the mobile communication device (eg, smartphone, tablet, etc.) capable of ultra-low output wireless. Alternatively, it allows it to communicate with other mobile or non-mobile network devices) and leverages the data present on the mobile device or the information collected by the cellular network to a central web server. Here, the data yields a numerically optimized radiation dose calculation and can be processed to use the mobile communication device GPS as needed, or the collected data can be processed using the mobile communication device CPU. It can be processed to result in a numerically optimized radiation dose calculation. Stand-alone sensor devices now have a limited low capacity that must be saved as much as possible to extend battery life. Ultra-low power wireless communication minimizes device power consumption for regular updates. In addition, the use of external mobile communication devices also limits the complexity of radiation sensors, as typical data or cellular communication antennas can consume significantly more power.

In one embodiment of the invention, the capabilities of an ultra-low power wireless transmission may be used to provide a processor for processing raw data (sensor readings) from an integrated sensor module wirelessly. Allows the transmission of measured sensor readings to compatible mobile devices (eg, smartphones or tablet devices, etc.) and processors for processing the raw data (sensor readings) of this information across wireless data networks. It is possible to send data to an Internet-based server that may be provided. This allows the analysis and reporting of measured doses for individual detectors using integrated sensor modules without the need to physically transport the dosimeter itself to a central location for readout and analysis, reducing costs. It can be reduced and minimize the time required to receive data and perform critical analysis. Embodiments of the present invention also allow multiple systems to receive many measured doses from many dosimeters with integrated sensor modules. The collection of sensor data from multiple systems enables temporal analysis and visualization of exposure sources and associated population-based trends, as well as geo-based mapping. An internet connection also allows remote update and troubleshooting of devices.

In one embodiment of the invention, the radiation dose calculation algorithm uses an optimization step to find a set of parameters (solution vectors) that best predict the unknown radiation field from a given dose reading. The best prediction of the field of irradiation is determined by using known field values to minimize the objective function. Optimization steps can be selected to optimize speed, accuracy or storage capacity as needed, and a single optimization step (eg, χ-square minimization algorithm) (which is the shortest amount of time and re-use). Achieve acceptable accuracy with a small amount of storage capacity), or iterative optimization procedures (eg, heuristic minimization algorithm) (which achieves better accuracy at the expense of more time and larger storage capacity utilization). ) Is used.

In one embodiment of the invention, the numerical optimization procedure is performed in a single step, where the objective function employs the form of a square difference between the measured and stored detector responses. The algorithm consists of predicting the irradiation field that would most likely produce the measurements by finding a solution vector that minimizes the chi-square function shown below. This is described in [16] and is incorporated herein by reference.

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Numerical optimization procedures can be performed using an iterative process. A well-known example of iterative optimization is regression using gradient descent [16]. However, such methods cannot easily incorporate heuristic rules to guide optimization procedures, and cannot ensure that they converge on solutions that meet known constraints. An example of an iterative numerical optimization procedure that allows the use of heuristic rules is the genetic algorithm [8]. The genetic algorithm can be used to find the optimal set of weighted parameters (solution vectors) for the proposed dose calculation algorithm. Genetic algorithms have been successfully used in automated image segmentation systems to find the optimal set of parameters to minimize energy functions used in Active Contour Models (ACM) and Level Set Methods (LSM). For example, in [8], Xu et al. Used a genetic algorithm to change the parameters of the ACM energy function until the contours generated by the ACM algorithm closely matched the practice set.

Another example of an iterative numerical optimization procedure is a class of heuristic optimization techniques known as the Harmony Algorithm [17]. Solution vectors in genetic algorithms are typically generated by combining two "parent" solution vectors that use evolutionary fit-based heuristic rules (ie, the two "parent" solution vectors are combined. , Generate a "child" solution vector). The harmony algorithm refines the genetic algorithm by extending the "parent" solution vector to a larger pool of potential solution vectors, which allows the harmony algorithm to converge to the optimal solution in a shorter amount of time. be able to.

In another embodiment of the invention, a harmony algorithm was used to execute the objective function shown below.

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(Reference) The following references are referenced above and are incorporated herein by reference. 1. Akselrod, MS, Lucas, AC, Polf, JC, McKeever, SWS, Optically stimulated luminescence of Al₂O₃: C, Radiation Measurements, 29, (3-4), 391-399 (1998). 2. Akslerod, MS, Kortov, VS, and Gorelova, EA, Preparation and properties of Al₂O₃: C, Radiat. Prot. Dosim. 47, 159-164 (1993). 3.Klemic, G., Bailey, P., Miller, K., Monetti, M., External radiation dosimetry in the aftermath of radiological terrorist event, Rad. Prot. Dosim, printing. 4.Lars Botter-Jensen et al., Optically Stimulated Luminescence Dosimetry, Elesevier (2003). 5. Stanford, N., Whole Body Dose Algorithm for the Landauer InLight Next Generation Dosimeter, Algorithm Revision: Next Gen IEC (September 13, 2010). 6. Stanford, N., Whole Body Dose Algorithm for the Landauer InLight Next Generation Dosimeter, Algorithm Revision: Next Gen NVLAP (September 27, 2010). 7.Stanford, N., Linear vs. Functional-Based Dose Algorithm Designs, Rad. Prot. Dosim., 144 (1-4), 253-256 (2011). 8.Xu, Yuan; Neu, Scott; Owens, Chester J .; Owens, Janis F .; Sklansky, Jack; Valentino, Daniel J., Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms . Proc. SPIE 4684, Medical Imaging 2002: Image Processing, 1406, May 15, 2002; doi: 10.1117 / 12.467106. 9. US Pat. No. 6,846,434 by Akselrod. 10. US Pat. No. 6,198,108 by Schwietzer et al. 11. US Pat. No. 6,172,368 by Tarr. 12. U.S. Pat. No. 6,127,685 by Yoder et al. 13. U.S. Pat. No. 5,739,541 by Kahilainen. 14. Miller, US Pat. No. 5,731,590. 15. US Patent Application No. 10 / 768,094 by Akselrod et al. 16.JA Snyman, Practical Mathematical Optimization: An introduction to Basic Optimization Theory and Classical and New Gradient-based Algorithms. Springer Publishing (2005); ISBN 0-387-24348-8. 17.XS Yang, Harmony Search as a Metaheuristic Algorithm, in: Music-Inspired Harmony Search Algorithm: Theory and Applications, Studies in Computational Intelligence, Springer Berlin, vol. 191, pp. 1-14 (2009).

Although the present invention has been described with reference to a particular embodiment, the present invention as numerous modifications, modifications, and modifications to the described embodiments are defined in the appended claims. It is possible without departing from the spirit and scope of the invention. Thus, the invention is not limited to the described embodiments, but it is intended to have the full range defined by the languages of the claims below and their equivalents.