Image diagnostic apparatus

Description: TECHNICAL FIELD [Detailed description of the invention]

【0001】

[Technical field to which the invention belongs]

The present invention relates to an image processing device that extracts an object region or contour based on image data of a subject imaged by an ultrasonic diagnostic device, MRI, or the like.

【0002】

[Conventional technology]

When extracting the contours of areas of interest and organs from biological images, binarization of images and edge detection are often used. As a method of extracting the contour by edge detection, as shown in FIG. 4, a method of detecting the edge radially from the reference position on the image and extracting the portion having strong edge strength as the contour can be mentioned. Fig. 10 schematically shows an example in which the contour of the ventricle was extracted from the tomographic image of the heart by this method. There are parts such as papillary muscles and chordae tendineae in the ventricle, and it is not possible to determine whether the detected edge is the edge of the myocardium or the edge of the chordae tendineae based on the edge information alone, and an incorrect contour is extracted. There was a problem of doing it.

【0003】

As a method of extracting an area by binarizing an image, there is a method of setting an area of interest and performing binarization. Figure 15 shows an example in which the region of interest is manually set to indicate the position of the ventricle, but since the region of interest is fixed, it is unnecessary for organs that move like the heart when contracted. There was a problem that it included various areas.

【0004】

Japanese Patent Application Laid-Open No. 9-122123 shows a method of detecting a position having a peak value in a pixel in a predetermined region as a pixel that is a boundary between the left ventricle and the left atrium of the heart. It was necessary to determine the boundary appropriately, and the peak value was not always shown at the boundary part, and it was difficult to detect the boundary stably.

【0005】

[Problems to be Solved by the Invention]

As described above, in the conventional contour extraction, there has been a problem of erroneous extraction of the contour due to the structure of the organ which cannot be discriminated only by the edge detection of the image. In addition, the fixed region of interest cannot always point to an appropriate region for a moving organ, and it is necessary to manually set an appropriate region of interest for a large number of images such as moving images. There were many operations and it was difficult. In addition, in the method of using the peak value of the pixel as a method of determining the boundary position between the ventricle and the atrium, the peak value may not always indicate the boundary position, and it is necessary to determine an appropriate search area in order to obtain good results. there were.

【0006】

Therefore, an object of the present invention is to detect the partial position of an organ from an image to prevent erroneous extraction of the contour due to the structure of the organ which cannot be discriminated only by the edge detection of the image, and to perform accurate contour extraction. It is possible. Another object of the present invention is to provide an image diagnostic apparatus capable of easily setting an appropriate region of interest for a moving organ. Another object of the present invention is to provide an image diagnostic apparatus capable of efficiently detecting the valve position by limiting the search range of the valve portion after detecting the ventricular range.

【0007】

[Means for solving problems]

The present invention has a ventricular range detecting means for detecting the range of the ventricle from the cardiac tomographic image, a valve position detecting means for detecting the position of the valve portion from the cardiac tomographic image, and a ventricle by correcting the contour shape by the early valve position. It is composed of a contour extraction means for extracting a contour or a region extraction means for extracting a region of interest including a ventricle.

【0008】

According to the present invention, it is possible to stably extract a specific part of an organ, prevent erroneous extraction of contours due to the structure of organs that cannot be discriminated only by edge detection of an image, and enable accurate contour extraction. It becomes. Regarding the setting of the region of interest, it becomes possible to easily set an appropriate region of interest according to the movement of the organ. In addition, the valve position can be detected efficiently.

【0009】

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing the structure of an image diagnostic apparatus to which the contour extraction method according to the embodiment of the present invention is applied, and FIG. 2 is a flow diagram showing the operation flow of the contour extraction method according to the embodiment of the present invention. is there. This embodiment is an example of using the contour extraction method, and is an diagnostic imaging apparatus that inputs a moving image of the heart, extracts the medial contour of the ventricle, and measures and displays the area of the cross section of the ventricle.

【0010】

In FIG. 1, 1 is an image input unit that performs image data input processing, 2 is an image memory that stores image data, 3 is a ventricular range detection unit that performs detection processing of a ventricular range in an image, and 4 is an image. A valve position detection unit that detects the position of the valve of the heart inside, 5 is a contour extraction unit that extracts the contour of the ventricle, and 6 is a measurement unit that calculates measurement values useful for diagnosis from the extracted contour information. , 7 are display units that display extracted contour information, measured information, and images.

【0011】

First, moving image data is input from the image input unit 1 and stored in the image memory 2. The operator inputs the approximate position of the cardiac ventricle in the image using a pointing device (not shown) or the like (S1). When the position where the heart is imaged is almost fixed, the input of the approximate position of S1 may be omitted and the preset coordinate values may be used as the approximate position. Next, the ventricular range is detected by the ventricular range detection unit 3 based on the approximate position of the ventricle (S2).

【0012】

As an example of the ventricular range detection process, a case where a contour model that converges to a portion having a high luminance value in an image is used will be described using the detailed flow shown in FIG. This contour model is a contour represented by a plurality of control points. For example, in the case of a heart image taken by an ultrasonic diagnostic apparatus, the myocardial portion has a high luminance value and the blood portion has a low luminance value.

【0013】

Therefore, in this method, the myocardial portion surrounding the ventricle, that is, the range of the ventricle is detected by using a contour model that converges on the portion having a high luminance value. For an image in which the myocardial portion has a lower brightness value than the blood portion, it is preferable to use a contour model that conversely converges on the lower brightness value portion in the image. The contents of the processing of ventricular range detection will be described. First, the search range of the ventricular range is determined based on the approximate position of the ventricle (S10).

【0014】

For the first frame of the moving image processing, the search range may be set for each control point using the approximate position, for example, as shown in FIG. For the second and subsequent frames of video processing, the search range may be set as shown in Fig. 4 as in the first frame, or the search range may be set as shown in Fig. 5 based on the outline of the previous frame. You may set it.

【0015】

Next, the pixels having the maximum brightness in the determined search range are searched, and contour candidates are generated by moving the control points to those pixel positions (S11). Next, the contour shape is smoothed (S12). The contour shape is smoothed in order to correct and search for a part that is partially erroneously extracted due to noise or the like. Next, if the amount of change in the contour shape is equal to or greater than the threshold value, the processes of S10, S11, and S12 are repeated. By making the search range smaller than the first time in the second and subsequent processing of S10 to S12, it is possible to generate a contour having the maximum brightness in the vicinity of the contour smoothed in the first processing. When the amount of change in the contour shape becomes equal to or less than the threshold value, the process is terminated (S13), and the ventricular range contour is determined.

【0016】

After the ventricular range is determined, the search range of the valve portion is determined (S3). Since the shape of the valve portion in the tomographic image of the heart has a characteristic image pattern as compared with other parts of the heart, it is effective to detect the valve portion. Images taken from the apex side of the transthoracic wall by an ultrasonic diagnostic device generally have the apex on the upper side of the image and the valve part on the lower side of the image. As shown above, the search range of the valve portion on the right side and the left side may be set. In an image captured by the transesophagus with an ultrasonic diagnostic apparatus, the upper side of the image is generally the valve portion and the lower side of the image is the apex of the heart. Therefore, for example, the right and left valve portions may be set as the search range as shown in FIG. In this way, the search range of the valve portion may be determined from the ventricular range and the like according to the posture of the heart. By determining the search range based on the ventricular range, the search range can be narrowed compared to searching the valve portion directly from the entire image, so that the processing can be speeded up and the detection rate can be improved.

【0017】

Next, the valve portion is detected from the search range determined by S3 (S4). The valve portion is detected by collating it with a dictionary image created from an image of the valve portion or the like (Fig. 8). The collation process may be performed by template matching, or a subspace method or a composite similarity method may be used. By the above processing, the position of the valve in the image is detected. Next, the initial contour shape for extracting the medial contour of the ventricle is calculated (S5).

【0018】

For example, the initial contour shape is set by correcting a part of the elliptical shape to the valve position as shown in FIG. 9, using the ventricular range set in S2 and the valve portion position detected up to S4. By detecting the valve portion position and using it for contour extraction in this way, it becomes possible to extract the correct contour without being caught by an erroneous structure in the ventricle, as compared with the case where the contour is searched only from the approximate position of the ventricle. ..

【0019】

Next, the image edge is detected near the initial contour corrected by the valve position, and the medial contour of the ventricle is extracted (S6). The medial contour of the ventricle is extracted from the moving image by performing the processing of S2 to S6 for all frames (S7). For the second and subsequent frames, it is efficient to generate the initial shape using the contour position of the previous frame.

【0020】

As a modification, when the distance between the valve position in the previous frame and the detection valve position in the current frame is greater than or equal to the threshold value when calculating the contour initial shape of S5, the contour initial shape is corrected by the valve position. However, if it is less than the threshold value, it is possible to correct the initial contour shape by the valve position. By controlling the application of the correction in this way, it is possible to stably extract the contour even when an erroneous valve position is detected. The contour extraction is completed by the above processing.

【0021】

Next, the cross-sectional area of the ventricle is calculated by the measuring unit 6 from the extracted contour information (S8), and displayed on the display unit 7 as shown in FIG. 12 (S9). The detected position and movement amount of the valve portion may be displayed in synchronization with an electrocardiogram or the like.

【0022】

In the present embodiment, the valve position can be efficiently detected by detecting the ventricular range, and the contour correction using the valve position prevents erroneous extraction of the ventricular contour as shown in FIG. It is possible to extract the contour with high accuracy, and it is possible to improve the accuracy of the measurement result in the subsequent stage.

【0023】

A second embodiment relating to the detection of the ventricular range of the present invention will be described. This embodiment is an example in which the region extraction method of the present invention is applied. Image diagnosis that automatically generates a region of interest by detecting the ventricular range and binarizes the pixel values in the region of interest to calculate the area of the ventricle region. This is an example of a device. FIG. 13 is a block diagram of the present embodiment, and FIG. 14 is a flow diagram showing a processing flow of the present embodiment.

【0024】

In FIG. 13, 1 is an image input unit that performs image data input processing, 2 is an image memory that stores image data, 3 is a ventricular range detection unit that performs detection processing of a ventricular range in an image, and 11 is detected. A binarization processing unit that binarizes the pixel values in the region of interest with the ventricular range as the region of interest, 12 is an area measurement unit that calculates the area of the ventricle from the binarized image data, and 13 is extracted. It is a display unit that displays contour information, measured information, and images.

【0025】

First, moving image data is input from the image input unit 1 and stored in the image memory 2. Similar to the first embodiment, the operator inputs the approximate position of the cardiac ventricle in the image using a pointing device or the like (not shown) (S21). When the position where the heart is imaged is almost fixed, the input of the approximate position of S21 may be omitted and the preset coordinate value may be used as the approximate position.

【0026】

Next, the ventricular range is detected by the ventricular range detection unit 3 based on the approximate position of the ventricle (S22). As the method for detecting the ventricular range, the method described in the first embodiment can be used. Further, the ventricular range may be determined by collation with a dictionary created from an image of the ventricle portion or the like. As a collation method, template matching, a subspace method, or a composite similarity method can be used as in the valve position detection in the first embodiment. The detected ventricular range is used as a region of interest in the following processes.

【0027】

Next, the pixel value in the region of interest is binarized with the ventricular region detected by the ventricular range detection unit as the region of interest (S23). In the case of an ultrasonic image, the brightness value of the myocardial part is generally high and the brightness value of the blood part is low, so the area of the blood part within the ventricle range is calculated from the number of low pixel values among the binarized pixel values. (S24). Next, the measurement results and images are displayed on the display unit 7 (S25).

【0028】

By detecting the ventricular range for each frame and setting it as the region of interest in this way, it is possible to measure with high accuracy because it does not include an extra part such as the atrium as compared with the conventional case where a fixed region of interest is used. .. In addition, it is not necessary to set the area of interest, and if you only specify a simple approximate position or adjust the display position of the organ so that it is almost constant, you do not need to enter the position at all, which greatly improves operability. ..

【0029】

In the above embodiments, the embodiment separated from the imaging device has been described, but it may be incorporated inside an ultrasonic diagnostic device or the like. It is also possible to add an image input function to the computer and realize the processing of the present invention by software.

【0030】

[Effect of the invention]

INDUSTRIAL APPLICABILITY According to the present invention, it is possible to accurately extract the contour of an organ and easily set an appropriate region of interest, and the efficiency of diagnosis and measurement is dramatically improved. Therefore, the effect is great.

[Simple explanation of drawings]

[Figure 1]

It is a block diagram of the 1st Embodiment which concerns on the contour extraction method of this invention.

[Figure 2]

It is a flow chart of the 1st Embodiment which concerns on the contour extraction method of this invention.

[Fig. 3]

It is a flow chart of the ventricular range detection part of 1st Embodiment.

[Fig. 4]

It is a figure which shows the example of the search range of an edge or a ventricle range.

[Fig. 5]

It is a figure which shows the example of the search range of a ventricular range.

[Fig. 6]

It is a figure which shows the example of the search range of a valve part.

[Fig. 7]

It is a figure which shows the example of the search range of a valve part.

[Fig. 8]

It is a figure which shows the detected valve part.

[Fig. 9]

It is a figure which shows the setting example of the contour initial shape.

[Fig. 10]

It is a figure which shows the example of the contour extracted by mistake.

[Fig. 11]

It is a figure which shows the example of the contour extracted correctly using the valve position.

[Fig. 12]

It is a figure which shows the display example of the measurement result.

[Fig. 13]

It is a block diagram of the 2nd Embodiment which concerns on the area extraction method of this invention.

[Fig. 14]

It is a flow chart of the 2nd Embodiment which concerns on the area extraction method of this invention.

[Fig. 15]

It is explanatory drawing of the example which contains the erroneous region by the fixed region of interest.

[Explanation of symbols]

1 Image input section 2 image memory 3 Ventricular range detector 4 Valve position detector 5 Contour extractor 6 Measuring unit 7 Display