JP2015228924A - Medical image processor and medical image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent overlooking of a lesion part.SOLUTION: According to an embodiment, a medical image processor comprises an extraction part, an identification part, a calculation part, a creation part, and a display part. The extraction part extracts from medical image data related to a subject an area of a three-dimensional tabular structure. The identification part identifies a plurality of cross sections orthogonal to a core wire in the extracted area from the medical image data. The calculation part calculates a morphological feature amount about the tabular structure for every identified cross section. The creation part creates a map image visually mapping the calculated feature amount. The display part displays the map image by superimposing it onto a medical image representing the tabular structure two-dimensionally.

Description

  Embodiments described herein relate generally to a medical image processing apparatus and a medical image processing method suitable for assisting catheterization.

  MPR (Multi Plane Reconstruction) image, CPR (Curved Planar Reconstruction) image, SPR (Stretched Curved Planar Reconstruction) image for observing tubular structures (blood vessels, trachea, upper digestive tract, lower digestive tract, etc.) in the subject An image, a MIP (Maximum / minimum Intensity Projection) image, a crosscut image, a fly-through image, or the like is used.

  A CPR image is an image depicting a specific blood vessel traveling two-dimensionally. The SPR image is an image expressed by straightening a line (for example, a blood vessel core line) along a blood vessel in the CPR image. The MIP image is an image obtained by performing projection processing on a three-dimensional image, and is an image in which the maximum value (or minimum value) of pixels in the projection direction is the pixel value of the projection image. A cross-cut image is a cross-sectional image cut along a cross section perpendicular to a blood vessel. The fly-through image is an image that expresses the appearance in the direction of the blood vessel at an arbitrary point in the blood vessel.

  These images are created by image processing 3D volume data acquired by, for example, an X-ray CT (Computed Tomography) apparatus or an MRI (Magnetic Resonance Imaging) apparatus. This kind of image can be created not only for blood vessels but also for other tubular structures.

  Using the three cross-sections displayed in the MPR image, the state of the wall and the lumen of the tubular structure can be observed. Using the CPR / SPR / cross-cut cross section, the state of the wall and the lumen can be observed. The state of the lumen can be observed using the fly-through image. As described above, even when it is difficult to grasp the whole image of the structure only by the CT / MRI cross section, various knowledge can be obtained by combining these images.

JP 2012-96024 A

  By the way, it is effective to rotate and observe a CPR / SPR image in order to find a lesion (such as a stenosis site or a thickened site) generated in a tubular structure. However, since there is no clue other than the displayed image, there is a possibility that even a skilled interpretation doctor may miss the lesion. In addition, since the interpretation doctor must view a large number of images by the operation of rotation, it may take time to observe.

  An object is to provide a medical image processing apparatus and a medical image processing method capable of preventing an oversight of a lesioned part.

  According to the embodiment, the medical image processing apparatus includes an extraction unit, a specifying unit, a calculation unit, a creation unit, and a display unit. The extraction unit extracts a region of a three-dimensional tubular structure from medical image data regarding the subject. The specifying unit specifies a plurality of cross sections orthogonal to the core line of the extracted region from the medical image data. A calculation part calculates the morphological feature-value regarding the said tubular structure for each of the specified cross section. The creation unit creates a map image in which the calculated feature amount is visually mapped. The display unit superimposes and displays the map image on a medical image expressing the tubular structure in two dimensions.

FIG. 1 is a diagram illustrating an example of an image diagnosis system to which the medical image processing apparatus according to the embodiment can be applied. FIG. 2 is a functional block diagram showing an example of the workstation 1 shown in FIG. FIG. 3 is a diagram illustrating an example of a medical image according to the embodiment. FIG. 4 is a flowchart illustrating an example of the processing procedure of the workstation 1. FIG. 5 is a diagram illustrating an example of a core line extracted for a bronchus. FIG. 6 is a diagram schematically illustrating an example of feature amounts that can be defined for each cross-cut image. FIG. 7 is a diagram illustrating an example of a medical image on which a map image is overlaid. FIG. 8 is a schematic diagram showing a process of displaying only a core line as a color map.

  FIG. 1 is a diagram illustrating an example of an image diagnosis system to which the medical image processing apparatus according to the embodiment can be applied. This system includes a CT apparatus 5, a workstation 1, and an X-ray image diagnostic apparatus 6. A workstation 1 as a medical image processing apparatus is connected to a CT apparatus 5 and an X-ray image diagnostic apparatus 6 via a network.

  In the embodiment, the CT apparatus 5 is used as a device for forming a medical image for supporting treatment. However, any other device may be used as long as it forms a medical image that can be used for support of treatment. For example, an MRI apparatus or a 3D (three-dimensional) angio apparatus may be used. In the embodiment, the image formed by the X-ray image diagnostic apparatus 6 is displayed on the workstation 1, but may be displayed on another monitor or the like instead.

  The X-ray diagnostic imaging apparatus 6 includes a bed on which a subject is placed, a gantry, an X-ray source that emits X-rays toward the subject, an X-ray detector that detects X-rays transmitted through the subject, A C-arm that holds the X-ray source and the X-ray detector facing each other is provided. The C-arm is attached to the gantry so as to be able to rotate about two axes that are substantially orthogonal to each other through the X-ray source and the X-ray detector.

  The workstation 1 acquires a medical image from the CT apparatus 5. Here, in this embodiment, in order to improve the processing speed of the workstation 1, a medical image is acquired in advance from the CT apparatus 5. However, the workstation 1 is necessary without acquiring a medical image in advance. A configuration may be used in which images that are sometimes required are acquired from the CT apparatus 5.

  The CT apparatus 5 irradiates the subject with X-rays and generates a medical image through arithmetic processing based on the intensity of the transmitted X-rays. In the embodiment, based on the three-dimensional image data (volume data) collected by the CT apparatus 5, a volume rendering image, a 2D (two-dimensional) projection image, a CPR image, an SPR image, a fly-through image, a MIP image, and a crosscut An image such as an image is generated. In addition, the CT apparatus 5 extracts a blood vessel based on a threshold value of the signal value, performs a thinning process on the blood vessel, and connects the centers of the inscribed circles at the thinned points to correspond to the blood vessel core line (approximately the center of the blood vessel). Line). This blood vessel core line is used as an example of a blood vessel line (lumen line) representing the running state of the blood vessel.

  FIG. 2 is a functional block diagram showing an example of the workstation 1 shown in FIG. The workstation 1 includes an overall control unit 101, an extraction unit 102, a specifying unit 103, a calculation unit 104, a creation unit 110, a display control unit 105, a user interface 106, and an image storage unit 109 as processing functions. Among these, the user interface 106 includes a display unit 107 and an input unit 108.

  The image storage unit 109 is a storage medium such as a hard disk or a memory. The image storage unit 109 includes 3D image data acquired by the CT apparatus 5 and, for example, a volume rendering image, a 2D projection image, a CPR image, and an SPR image (CPR / SPR image) generated based on the 3D medical image data. ), Medical images such as fly-through images, MIP images, and cross-cut images are stored.

  3A shows an example of an SPR image, FIG. 3B shows an example of a cross-cut image, and FIG. 3C shows an example of a fly-through image. Both are images generated by performing image processing on the three-dimensional image data acquired by the CT apparatus 5.

  The overall control unit 101 controls the operation of each functional unit. The overall control unit 101 receives, for example, a display image type designation input by an operator using the input unit 108. The operator designates an image type such as an MPR image, a CPR image, or an SPR image while referring to the X-ray image currently generated by the X-ray image diagnostic apparatus 6. The designated image is displayed on the display unit 107.

  The extraction unit 102 extracts a region of a three-dimensional tubular structure in the body of the subject from medical image data stored in the image storage unit 109 regarding the subject. In the embodiment, a blood vessel is described as an example of a tubular structure. In addition, in the embodiment, the trachea, bronchi, or digestive tract can be handled in the same manner. Further, the extraction unit 102 extracts the extracted blood vessel core line (blood vessel core line) by a calculation process based on an existing technique.

  The specifying unit 103 specifies a plurality of cross-sectional images orthogonal to the extracted blood vessel core line, that is, a plurality of cross-cut images, from the medical image data. Cross-cut images are stored in the image storage unit 109 in association with points on the blood vessel core line.

  The calculation unit 104 calculates a morphological feature amount related to the extracted blood vessel for each of the identified crosscut images. That is, the calculation unit 104 calculates, for each blood vessel cross section appearing in the crosscut image, a feature amount that can express, for example, a stenosis of the blood vessel. First, the calculation unit 104 extracts the lumen and outer wall of the blood vessel from the crosscut image. In addition to the manual method by the operator, any known method such as a semi-automatic method using a region expansion method or the like or a fully automatic method may be used in addition to the manual method by the operator.

  Next, the calculation unit 104 calculates a feature quantity that can specifically represent stenosis. As the feature amount, for example, the ratio of the major axis to the minor axis in the annular blood vessel image, the lumen area, the outer wall area, the curvature, the circularity, the skewness, the kurtosis, the ratio of the lumen area to the outer wall area, the wall There are a thickness, an average CT value, a maximum / minimum CT value, a ratio with a neighboring cross section in various feature amounts, and the like. In addition to this, the feature amount may be any amount as long as it is a value capable of calculating the medical and clinical features of the blood vessel from the image.

  The creation unit 110 creates a map image in which the feature amount calculated by the calculation unit 104 is visually mapped in accordance with, for example, the blood vessel position in the CPR / SPR image. A CPR / SPR image is an example of a medical image that represents a blood vessel in two dimensions.

  The display control unit 105 superimposes (overlays) the map image created by the creation unit 110 on the CPR / SPR image and displays the map image on the display unit 107. Next, the operation of the above configuration will be described.

  FIG. 4 is a flowchart illustrating an example of the processing procedure of the workstation 1. In FIG. 4, the workstation 1 acquires CT image data from the CT apparatus 5 and stores it in the image storage unit 109 (step S1). Next, the extraction unit 102 extracts a blood vessel as a tubular structure from the acquired CT image data (step S2), then extracts a blood vessel core line and stores the core line information in the image storage unit 109 (step S3).

  Examples of the method for extracting blood vessels in step S2 include a manual method, a semi-automatic method using a region expansion method after one click by the user, a fully automatic method, and the like. Any known algorithm is used. May be. In addition, examples of the method for extracting the core line region in step S3 include a manual method, a semi-automatic method of interpolating between points after a user clicks a plurality of points, and a fully automatic method using distance conversion. Any algorithm may be used. FIG. 5 is a diagram illustrating an example of a core line extracted for a bronchus.

  Next, the workstation 1 creates a CPR / SPR image using the core line information (step S4). These created images are stored in the image storage unit 109. When the processing so far is completed, the workstation 1 starts the procedure of step S5. The procedure of step S5 includes steps S51, S52 and S53.

  In step S <b> 5, the specifying unit 103 specifies a plurality of crosscut images orthogonal to the extracted blood vessel core line from the medical image data. As shown in FIG. 6A, the crosscut images are associated with each point on the blood vessel core line expressed by CPR, and the number of crosscut images corresponding to the number of points is specified. The calculation unit 104 extracts a blood vessel wall for each crosscut image. By this processing, for example, a shape showing the cross section of the blood vessel as shown in FIG. 6B is extracted.

  Next, the calculation unit 104 acquires the length of the major axis and the length of the minor axis for each graphic shown in FIG. 6B, and calculates the ratio (ratio) (step S51). That is, a value obtained by dividing the length of the short axis by the length of the long axis is used as the feature amount. As shown in FIG. 6C, the feature quantity of the smooth cross section is 0.9, whereas the feature quantity of the cross section having unevenness is a value of 0.5 or 0.4.

  When the feature values for all the cross sections (cross-cut images) are calculated, the creation unit 110 creates a map image that represents each pixel with a color according to the feature value. In the example shown in FIG. 6, the greater the feature value, the lower the possibility of stenosis of the blood vessel, and the smaller the feature value, the higher the possibility of stenosis. Therefore, the creation unit 110 associates the possibility of stenosis with the color, and maps, for example, a portion having a large feature amount in blue and a portion having a small feature amount in red. In the monochrome display of FIG. 6D, it is understood that a lightly colored portion is close to red and a darkly colored portion is close to blue. In this way, the possibility of the presence of a stenosis site can be expressed by a color map.

  FIG. 6 illustrates a CPR image, but the original image may be a general MPR image, an SPR image, a 3D rendering image, or the like in addition to the CPR. The color map can be created by changing the transparency or changing the LUT.

  When the map image is created, the display control unit 105 superimposes (overlays) the map image on the CPR / SPR image created in step S4 and displays it on the display unit 107 (step S53). Thus, the periphery of the stenosis region included in the CPR / SPR image is displayed in a color map with a color indicating the possibility of stenosis. Therefore, the operator can grasp at a glance the possibility of stenosis occurring in the blood vessel.

  FIG. 7 is a diagram illustrating an example of a medical image on which a map image is overlaid. FIG. 7A shows an overlay display of the color map over the entire region of the trachea. FIG. 7B displays a color map only on the core line of the trachea. In the display mode of FIG. 7, the amount of information in the background portion (the region where the color map is not overlaid) is larger in (b) than in (a). In other words, there are few parts hidden in the color map.

  FIG. 8 is a schematic diagram showing a process of displaying only a core line as a color map. By performing a convolution operation on the core line of the tubular structure and the color map data, a color map image that can be overlaid only on the core line can be created.

  As described above, in the embodiment, a cross section orthogonal to the tubular structure is specified from the medical image, and the shape and composition of the tubular structure projected on the cross section are reflected for each cross section along the core line of the tubular structure. Calculate features. Then, a map image in which the feature value and color are associated with each other is created, and the map image is overlaid on the image displaying the tubular structure.

Since it did in this way, an operator and an image interpretation doctor can grasp the whole picture of a tubular structure at a glance at a glance. In addition, the area with stenosis or thickening is displayed in a considerable color, so it is easy to find the lesion, and the risk of oversight is greatly reduced without processing such as rotating the image. Can do. Furthermore, the diagnostic speed can be increased by making it easier to observe the image, and the throughput can be improved.
Accordingly, it is possible to provide a medical image processing apparatus and a medical image processing method that can prevent oversight of a lesion.

  The present invention is not limited to the above embodiment. For example, in the embodiment, the workstation 1 is provided as a medical image processing apparatus separately from the CT apparatus 5, but a configuration in which the function of the medical image processing apparatus is directly incorporated in a medical image diagnostic apparatus such as the CT apparatus 5 may be used.

  It is also possible to omit the processing in step S2 in FIG. 4 and determine the core wire using a manual core wire determination or a core wire extraction algorithm that does not require a tubular structure. In step S4, not only a CPR image but also an MPR image, an SPR image, or a 3D rendering image can be used.

  Alternatively, a plurality of feature amounts may be calculated, and an image that is individually color mapped for each feature amount may be created and displayed in a switched manner. For example, an image that is displayed in reddish in a portion with a higher degree of stenosis and an image that is displayed in bluish in a portion with a higher degree of thickening may be switched according to the operation of the operator.

  In the embodiment, the lumen or the core wire of the tubular structure is displayed in a color map, but the wall of the tubular structure may be displayed in a color map. Furthermore, the area where the color map is overlaid may be switched between the lumen, the core, and the wall. In this way, it is possible to prevent a region of clinical interest from being hidden by the map image and becoming invisible.

  In the embodiment, the color map in which the feature amount and the color are associated with each other has been described. However, a single color shading map (for example, a monochrome gray scale map) may be used. That is, the feature value and the shading may be associated with each other.

  In addition, a cross-cut image where the feature value indicates a predetermined value may be superimposed on the medical image and displayed on the display unit 107. Further, the color map may be overlaid only on the portion where the feature amount is in a predetermined range. For example, only a predetermined range in which the feature value indicating the degree of stenosis is defective may be displayed. In this way, the color map can be overlaid only on the dangerous area, so that the target area can be narrowed down. Furthermore, when the color map is designated with the mouse pointer, the crosscut image at that position may be automatically displayed. Alternatively, one cross-sectional image in a predetermined range in which the feature value indicating the degree of stenosis is defective may be automatically displayed.

  Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. The novel embodiment can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. This embodiment and its modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 ... Workstation, 5 ... CT apparatus, 6 ... X-ray diagnostic imaging apparatus, 101 ... General control part, 102 ... Extraction part, 103 ... Identification part, 104 ... Calculation part, 105 ... Display control part, 106 ... User interface, 107: display unit, 108: input unit, 109: image storage unit, 110: creation unit.

Claims (16)

An extraction unit for extracting a region of a three-dimensional tubular structure from medical image data relating to the subject;
A specifying unit that specifies, from the medical image data, a plurality of cross sections orthogonal to the core line of the extracted region;
A calculation unit for calculating a morphological feature amount related to the tubular structure for each of the identified cross sections;
A creation unit for creating a map image in which the calculated feature amount is visually mapped;
A medical image processing apparatus comprising: a display unit configured to superimpose and display the map image on a medical image expressing the tubular structure in two dimensions. The calculation unit calculates, for each of the cross sections, first and second feature quantities different from each other with respect to the tubular structure,
The creation unit creates the map image for each of the calculated first and second feature amounts,
The display unit switches and displays either the created map image of the first feature value or the map image of the second feature value superimposed on the medical image. The medical image processing apparatus according to 1.   The medical image processing apparatus according to claim 1, wherein the creation unit creates the map image by mapping feature amounts in a predetermined range.   The medical image processing apparatus according to claim 1, wherein the display unit further superimposes and displays a cross-sectional image corresponding to a predetermined feature amount on the medical image.   The medical image processing apparatus according to claim 1, wherein the creation unit creates the map image by mapping the feature quantity along the core line in the medical image.   The medical image processing apparatus according to claim 1, wherein the creating unit creates the map image by mapping the feature amount along a wall of the tubular structure in the medical image.   The medical image processing apparatus according to claim 1, wherein the display unit displays the map image in color on the medical image.   The medical image processing apparatus according to claim 1, wherein the display unit displays the map image in gray scale on the medical image. Extracting a region of a three-dimensional tubular structure from medical image data relating to the subject;
Identifying a plurality of cross sections orthogonal to the core line of the extracted region from the medical image data;
For each of the identified cross sections, calculate a morphological feature related to the tubular structure;
Creating a map image visually mapping the calculated feature amount;
A medical image processing method, wherein the map image is superimposed and displayed on a medical image expressing the tubular structure in two dimensions. The calculation unit calculates, for each of the cross sections, first and second feature quantities different from each other with respect to the tubular structure,
The creating includes creating the map image for each of the calculated first and second feature amounts,
The display is characterized in that either the created map image of the first feature value or the map image of the second feature value is superimposed and displayed on the medical image. Item 10. The medical image processing method according to Item 9.   The medical image processing method according to claim 9, wherein the creating includes creating the map image by mapping feature amounts in a predetermined range.   The medical image processing method according to claim 9, wherein the displaying further displays a cross-sectional image corresponding to a predetermined feature amount on the medical image.   The medical image processing method according to claim 9, wherein the creating includes creating the map image by mapping the feature amount along the core line in the medical image.   The medical image processing method according to claim 9, wherein the creating includes creating the map image by mapping the feature amount along a wall of the tubular structure in the medical image.   The medical image processing method according to claim 9, wherein the displaying displays the map image in color on the medical image.   The medical image processing method according to claim 9, wherein the displaying includes displaying the map image in a gray scale on the medical image.