Program, information processing method and information processing apparatus

Abstract

To provide a program, etc. for accurately calculating a representative value for a blood vessel.SOLUTION: A program causes a computer to perform processes of: acquiring a plurality of transverse tomographic images 58 of a blood vessel captured by a catheter inserted in the blood vessel at different positions along a longitudinal direction of the blood vessel; detecting one or more objects from each of the transverse tomographic images 58; on the basis of each of the objects detected from the plurality of transverse tomographic images 58, constructing a three-dimensional shape of the object; determining a centroidal line 68 of the three-dimensional shape of one of the objects; and on the basis of a cross section obtained by cutting a plane perpendicular to the centroidal line 68, determining a representative value of the one or more objects on the plane.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a program, an information processing method, and an information processing device. [Background technology]

[0002] A method has been disclosed for presenting the minimum lumen area of ​​a blood vessel based on a plurality of tomographic images taken using an image acquisition catheter inserted into the blood vessel (Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-62212 Summary of the Invention [Problem to be solved by the invention]

[0004] In the method of Patent Document 1, the imaging catheter is inserted parallel to the blood vessel, and the minimum lumen area is calculated on the assumption that the captured tomographic image is perpendicular to the blood vessel.

[0005] However, because blood vessels are curved, the imaging catheter may be tilted relative to the blood vessel inside the blood vessel. In such a case, the captured tomographic image is also tilted relative to the blood vessel. From the tomographic image tilted relative to the blood vessel, it is not possible to correctly calculate representative values ​​related to the blood vessel, such as the lumen area.

[0006] In one aspect, an object of the present invention is to provide a program or the like for accurately calculating a representative value related to blood vessels. [Means for solving the problem]

[0007] The present invention relates to (1) acquiring a plurality of cross-sectional images of a blood vessel at different positions along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting one or more objects in each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; Based on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity, a representative value of the one or more objects on the plane is determined. It is a program that causes a computer to execute processing.

[0008] Here, an embodiment of the present invention is (2) The program described in (1) above, Preferably, the object includes a blood vessel lumen, an external elastic lamina, a blood vessel adventitia, or a stent.

[0009] (3) The program according to (1) or (2) above, The three-dimensional shape is The object detected from each of the plurality of cross-sectional images is disposed at a position corresponding to the cross-sectional image; Smoothing the placed object Preferably, it is constructed by processing.

[0010] (4) The program according to any one of (1) to (3) above, The center of gravity line is Calculating a center of gravity of a smoothed object obtained by cutting the three-dimensional shape along a plane corresponding to the cross-sectional image; It is preferable to determine the center of gravity so as to connect the center of gravity points calculated on the planes corresponding to the plurality of transverse cross-sectional images.

[0011] (5) The program according to any one of (1) to (4) above, Calculating a distance between an intersection point of the transverse cross-sectional image and the center of gravity line and a center of the catheter in each of the transverse cross-sectional images; Preferably, the blood vessel is divided into a plurality of segments along the length of the blood vessel based on the calculated distance.

[0012] (6) The program described in (5) above, determining attributes of each of the divided segments based on a relationship between the center line and a center line of the catheter; It is preferable to determine whether a representative value of the object in the cross-sectional view or a representative value of the object in the cross-sectional image is determined based on the determined attribute.

[0013] (7) The program according to (5) or (6) above, constructing a solid shape of the object for each of the segments; It is preferable to interpolate the three-dimensional shape between adjacent segments.

[0014] (8) The program according to any one of (5) to (7) above, Accepting a selection of one transverse cross-sectional image from the plurality of transverse cross-sectional images acquired; determining the segment in which the selected cross-sectional image is included; It is preferable to use the cross-sectional images contained in the determined segments to construct a three-dimensional shape of the object.

[0015] (9) The program according to any one of (1) to (8) above, It is preferable that the representative value of an object determined based on the cross-sectional view and the representative value of the object in the cross-sectional image are displayed in different manners.

[0016] (10) The program according to any one of (1) to (9) above, It is preferable to display a graph using the position of the transverse cross-sectional image along the longitudinal direction of the blood vessel as a first axis, and using a representative value of the object in a plane passing through the intersection of the transverse cross-sectional image and the center of gravity line and perpendicular to the center of gravity line as a second axis perpendicular to the first axis.

[0017] (11) The program according to any one of (1) to (10) above, It is preferable to construct a three-dimensional shape of the blood vessel by using the center line in a first direction and arranging cross sections of the blood vessel in a plane that passes through the intersection of the transverse layer image and the center line and is perpendicular to the center line in a second direction perpendicular to the first direction.

[0018] (12) The information processing method is acquiring a plurality of cross-sectional images of the blood vessel along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting an object from each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; Based on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity, a representative value of the object on the plane is determined. Preferably, the processing is computer implemented.

[0019] (13) The information processing device comprises: An information processing device including a control unit, The control unit is acquiring a plurality of cross-sectional images of the blood vessel at different positions along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting one or more objects in each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; It is preferable to determine a representative value of the one or more objects on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity line. Effect of the Invention

[0020] In one aspect, it is possible to provide a program or the like that accurately calculates a representative value related to a blood vessel. [Brief description of the drawings]

[0021] [Figure 1] FIG. 11 is an explanatory diagram illustrating an overview of a process for calculating a representative value. [Diagram 2] FIG. 2 is an explanatory diagram illustrating a configuration of an information processing device. [Diagram 3] FIG. 2 is an explanatory diagram for explaining a record layout of a tomographic image DB. [Figure 4] FIG. 11 is an explanatory diagram illustrating a procedure for creating classification data. [Diagram 5] 11 is a flowchart illustrating a process flow of a program. [Figure 6] This is a display example. [Figure 7] FIG. 11 is an explanatory diagram illustrating a blood vessel according to the second embodiment. [Figure 8] 8 is an explanatory diagram showing a schematic longitudinal section of a three-dimensional image constructed by the three-dimensional scanning shown in FIG. 7. [Figure 9] FIG. 11 is an explanatory diagram for explaining the center distance. [Figure 10] 13 is an example of a graph showing the relationship between the acquisition position of a transverse cross-sectional image and the center-to-center distance W. [Figure 11] 10 is a flowchart illustrating the flow of processing of a program according to the second embodiment. [Figure 12] 10 is a flowchart illustrating a process flow of a tomographic image processing subroutine. [Figure 13] 13 is a flowchart illustrating a process flow of a segment division subroutine. [Figure 14]13 is a flowchart illustrating a process flow of a type determination subroutine. [Figure 15] FIG. 11 is an explanatory diagram for explaining a method of connecting segments. [Figure 16] 13 is a flowchart illustrating the flow of processing of a program according to a third embodiment. [Figure 17] FIG. 13 is an explanatory diagram for explaining a three-dimensional image construction procedure according to the fourth embodiment. [Figure 18] 13 is a flowchart illustrating the flow of processing of a program according to a fourth embodiment. [Figure 19] FIG. 13 is an explanatory diagram illustrating a configuration of an information processing device according to a fifth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] [Embodiment 1] FIG. 1 is an explanatory diagram for explaining an overview of the process of calculating the representative value. A user such as a doctor inserts an image acquisition catheter 16 (see FIG. 7) into a blood vessel 15 (see FIG. 7). The image acquisition catheter 16 is for three-dimensional scanning, and can continuously capture a plurality of transverse cross-sectional images 58 in which the scanning plane is changed little by little in the axial direction. In the following description, a transverse cross-sectional image 58 created in one three-dimensional scanning may be referred to as a set of transverse cross-sectional images 58. Similarly, the interval between the transverse cross-sectional images 58 may be referred to as a slice thickness.

[0023] In addition, in Fig. 1, a transverse layer image 58 in a so-called XY (orthogonal coordinate) format constructed according to an actual shape is illustrated as an example. The transverse layer image 58 may be in a so-called RT (polar coordinate) format constructed by arranging scanning lines in parallel in the order of scanning angles. Conversion between the RT format and the XY format may be performed during the process described using Fig. 1. The method of conversion between the RT format and the XY format is well known, so the description will be omitted.

[0024] Based on each transverse cross-sectional image 58, classification data 57 is created. The classification data 57 is data obtained by classifying each pixel constituting the transverse cross-sectional image 58 into a plurality of regions, such as the lumen region 41, the biological tissue region 43, the catheter region 44, and the extraluminal region 45. The center of the catheter region 44 corresponds to the central axis of the image acquisition catheter 16. The regions shown in FIG. 1 are examples of regions constituting the classification data 57. The classification data 57 may include, for example, a guidewire region, a stent region, a calcification region, and a plaque region.

[0025] Based on the classification data 57, a classification image can be created in which the pixels constituting the transverse cross-sectional image 58 are colored differently for each region. A set of classification images is created based on a set of transverse cross-sectional images 58. The classification images obtained by visualizing the classification data 57 are illustrative diagrams showing the cross-sectional shapes of blood vessels 15. A method for creating the classification data 57 will be described in detail later.

[0026] Each of the regions constituting the classification data 57 is an example of a region corresponding to an object detected from the transverse cross-sectional image 58. The control unit 21 (see FIG. 2) can detect an object depicted in the transverse cross-sectional image 58 by creating the classification data 57 based on the transverse cross-sectional image 58.

[0027] In the following description, the region formed by combining the lumen region 41 and the catheter region 44 will be referred to as a combined lumen region 49. The combined lumen region 49 indicates the region inside the biological tissue region 43. The combined lumen region 49 is also an example of a region corresponding to an object.

[0028] The control unit 21 may use, for example, the lumen region 41, the biological tissue region 43, the inner boundary of the biological tissue region 43, the outer boundary of the biological tissue region 43, the inner boundary of the extraluminal region 45, or the stent region, etc., as the object. Note that the inner boundary of the biological tissue region 43 corresponds to the inner wall of a blood vessel.

[0029] The boundary line of the outer surface of the biological tissue region 43 corresponds to the blood vessel outer wall. The blood vessel outer wall includes the external elastic lamina and the vascular adventitia. When an IVUS (Intravascular Ultrasound) catheter is used as the image acquisition catheter 16, the external elastic lamina in the transverse layer image 58 is an EEM (External Elastic Membrane). When an OFDI (Optical Frequency Domain Imaging) catheter is used as the image acquisition catheter 16, the external elastic lamina in the transverse layer image 58 is an EEL (External Elastic Lamina).

[0030] The control unit 21 constructs a three-dimensional image 51 based on a set of classification data 57. Specifically, the control unit 21 arranges the classification data 57 in a three-dimensional space with intervals corresponding to the slice thickness. The control unit 21 converts each pixel constituting the classification data 57 into voxels with a thickness. The control unit 21 constructs a three-dimensional model by interpolating between the voxels. The control unit 21 performs spatial smoothing processing on the three-dimensional model.

[0031] In this manner, a three-dimensional image 51 is generated in which the effects of noise and the like caused by the shaking of the image acquisition catheter 16 due to pulsation and by inference using a classification model 31 (see FIG. 4) described later are reduced.

[0032] The three-dimensional image 51 includes the three-dimensional shape of the blood vessel 15. The three-dimensional image 51 can be cut at any cross section. The three-dimensional image 51 shown in the lower part of Fig. 1 is a schematic diagram of a cross section obtained by cutting the three-dimensional image 51 at a plane including the central axis.

[0033] In the following description, each object constituting the three-dimensional image 51 will be referred to as a smoothed object. Similarly, a cross section of the three-dimensional image 51 cut at a position corresponding to the classification data 57 will be referred to as smoothed classification data 571.

[0034] The smoothed object includes a smoothed biological tissue region 431 corresponding to the region obtained by smoothing biological tissue region 43, a smoothed extraluminal region 451 corresponding to the region obtained by smoothing extraluminal region 45, and a smoothed combined lumen region 491. The smoothed combined lumen region 491 is a region combining a smoothed lumen region 411 corresponding to the region obtained by smoothing lumen region 41, and a smoothed catheter region 441 corresponding to the region obtained by smoothing catheter region 44.

[0035] The control unit 21 calculates the center of gravity 67, which is the center of gravity of the smoothed combined lumen region 491, for each of the smoothed classified data 571. The method of calculating the center of gravity of a planar figure is well known, and therefore detailed description thereof will be omitted.

[0036] In addition, the region used for the object for calculating the center of gravity 67 is not limited to the smoothed combined lumen region 491, but it is desirable for it to be a region that surrounds the entire circumference of the image acquisition catheter 16 over almost the entire length of the range depicted in the set of transverse cross-sectional images 58.

[0037] When constructing the three-dimensional image 51 from a set of classification data 57 by the above-mentioned method, it is assumed that the image acquisition catheter 16 is linear and all the classification data 57 are parallel surfaces. Therefore, the catheter region 44 extends straight in the longitudinal direction along the central axis of the three-dimensional image 51. In other words, the central axis of the three-dimensional image 51 indicates the central axis of the image acquisition catheter 16.

[0038] The lumen region 41 is a blood flow region into which the image acquisition catheter 16 is inserted, and corresponds to the blood vessel lumen. The biological tissue region 43 corresponds to the blood vessel 15 surrounding the blood flow region. In the three-dimensional image 51 shown in Fig. 1, the smoothed biological tissue region 431 is depicted in a meandering state relative to the smoothed catheter region 441. The classification data 57 and the smoothed classification data 571 are inclined with respect to the central axis of the smoothed biological tissue region 431.

[0039] Therefore, the representative value of an object calculated based on classification data 57 or smoothed classification data 571 includes an error due to the slope of classification data 57 or smoothed classification data 571. The representative value of an object is, for example, the area of ​​lumen region 41, the area of ​​combined lumen region 49, the area of ​​smoothed lumen region 411, or the area of ​​combined lumen region 491.

[0040] The control unit 21 determines a center line 68 connecting the center points 67 calculated for each of the smoothed classification data 571. Note that in Fig. 1, the center points 67 are lined up on the same plane, and the center line 68 is illustrated as if it were a curve on the plane, but in reality, the center points 67 are distributed in front of and behind the plane shown in Fig. 1, and the center line 68 is a three-dimensional curve.

[0041] The control unit 21 determines an evaluation plane that passes through each center of gravity 67 and is perpendicular to the center of gravity line 68. The control unit 21 generates corrected classification data 54, which is a cross-sectional view of the three-dimensional image 51 cut by the evaluation plane. The control unit 21 calculates a representative value of the object based on the corrected classification data 54. As a result, the control unit 21 can accurately calculate a representative value that appropriately reflects the state of the blood vessel 15.

[0042] The control unit 21 may calculate the representative value of an object using a smoothed object different from the smoothed object used to calculate the center of gravity 67. For example, the control unit 21 determines the center of gravity line 68 and the evaluation plane using the center of gravity 67 of the smoothed combined lumen region 491 as described above. The control unit 21 may calculate a representative value for a smoothed object different from the combined lumen region 49, such as a calcified region on the evaluation plane.

[0043] 2 is an explanatory diagram for explaining the configuration of the information processing device 20. The information processing device 20 includes a control unit 21, a main memory device 22, an auxiliary memory device 23, a communication unit 24, a display unit 25, an input unit 26, and a bus. The control unit 21 is an arithmetic and control device that executes the program of this embodiment. The control unit 21 uses one or more central processing units (CPUs), graphics processing units (GPUs), multi-core CPUs, or the like. The control unit 21 is connected to each hardware unit constituting the information processing device 20 via the bus.

[0044] The main memory device 22 is a storage device such as an SRAM (Static Random Access Memory), a DRAM (Dynamic Random Access Memory), a flash memory, etc. The main memory device 22 temporarily stores information required during processing performed by the control unit 21 and programs being executed by the control unit 21.

[0045] The auxiliary storage device 23 is a storage device such as an SRAM, a flash memory, a hard disk, or a magnetic tape. A tomographic image DB (Database) 36, programs to be executed by the control unit 21, and various data required for executing the programs are stored in the auxiliary storage device 23. The tomographic image DB 36 may be stored in an external large-capacity storage device connected to the information processing device 20. The communication unit 24 is an interface that performs communication between the information processing device 20 and a network.

[0046] The display unit 25 is, for example, a liquid crystal display panel or an organic EL (electro-luminescence) panel, etc. The input unit 26 is, for example, a keyboard, a mouse, a pen tablet, etc. The display unit 25 and the input unit 26 may be stacked to form a touch panel.

[0047] The information processing device 20 is a general-purpose personal computer, a tablet, a mainframe computer, a virtual machine running on a mainframe computer, or a quantum computer. The information processing device 20 may be configured with hardware such as a plurality of personal computers or a mainframe computer that perform distributed processing. The information processing device 20 may be configured with a cloud computing system. The information processing device 20 may be configured with hardware such as a plurality of personal computers or a mainframe computer that operate in cooperation with each other.

[0048] 3 is an explanatory diagram for explaining the record layout of the tomogram DB 36. The tomogram DB 36 is a database in which transverse images 58 created by three-dimensional scanning and classification data 57 are recorded. The tomogram DB 36 has a 3D scan ID field, a tomogram number field, a tomogram field, and a classification data field. The tomogram field and the classification data field each have an RT format field and an XY format field.

[0049] The 3D scan ID field records a 3D scan ID assigned to each three-dimensional scan. The slice number field records a number indicating the order of the cross-sectional images 58 created in one three-dimensional scan. The RT format field of the cross-sectional image field records the cross-sectional images 58 in RT format. The XY format field of the cross-sectional image field records the cross-sectional images 58 in XY format. The RT format field of the classification data field records classification data 57 in RT format. The XY format field of the classification data field records classification data 57 in XY format.

[0050] In addition, only the transverse cross-sectional image 58 in the RT format is recorded in the tomographic image DB 36, and the control unit 21 may create the transverse cross-sectional image 58 in the XY format by coordinate conversion as necessary. Instead of the DB in which the transverse cross-sectional image 58 is recorded, a DB in which data related to the scanning line before the transverse cross-sectional image 58 is created may be used.

[0051] Similarly, only one of the classification data 57 in the RT format and the classification data 57 in the XY format may be recorded in the tomographic image DB 36, and the control unit 21 may create the other classification data 57 by coordinate conversion as necessary. Instead of the transverse cross-sectional image 58, a DB in which data related to the scanning line before creating the transverse cross-sectional image 58 is recorded may be used. The tomographic image DB 36 may not have a tomographic image field, and only the classification data 57 created based on the transverse cross-sectional image 58 may be recorded.

[0052] In this embodiment, a case will be described as an example in which the transverse image 58 acquired by the image acquisition catheter 16 is automatically recorded in real time in the tomographic image field of the tomographic image DB 36. The control unit 21 reads out the transverse image 58 from the tomographic image DB 36, and records the created classification data 57 in the tomographic image DB 36.

[0053] The control unit 21 sequentially performs the processing described with reference to Fig. 1 based on the classification data 57 to calculate the representative value. As described above, after the three-dimensional scanning by the image acquisition catheter 16 is completed, the control unit 21 can quickly calculate the representative value. The control unit 21 causes the display unit 25 to display the calculated representative value. The control unit 21 may also cause the display unit 25 to display the calculated representative value on a screen of an imaging diagnostic device connected to the image acquisition catheter 16. The imaging diagnostic device is, for example, an ultrasound diagnostic device or an OCT diagnostic device.

[0054] The tomographic image DB 36 may be created during a time period when the information processing device 20 has plenty of processing capacity, such as late at night. The tomographic image DB 36 may be created by hardware separate from the information processing device 20. The control unit 21 reads out the classification data 57 recorded in the classification data field of the tomographic image DB 36, performs the processing described with reference to FIG. 1, and calculates a representative value.

[0055] 4 is an explanatory diagram for explaining the procedure for creating classification data. The classification model 31 is a model that receives an input of a transverse cross-sectional image 58 and assigns, to each pixel constituting the transverse cross-sectional image 58, a label relating to the region depicted in that pixel. The classification model 31 may be a model that assigns a label to each small region composed of a plurality of pixels.

[0056] The classification model 31 is generated by a known machine learning method such as semantic segmentation using a training data DB in which multiple sets of transverse images 58 and classification data 57 created by a user skilled in interpreting the transverse images 58 are recorded. For the training data DB, a database having a similar configuration to the tomographic image DB 36 described using FIG. 3 can be used.

[0057] The classification model 31 may be configured by combining a plurality of models, such as a model that outputs the probability that each pixel is a lumen region 41, a model that outputs the probability that it is not a lumen region 41, a model that outputs the probability that it is a biological tissue region 43, and a model that outputs the probability that it is not a biological tissue region 43. The classification model 31 may be configured to output, for each small region, a sequence that lists the probability that it is a lumen region 41, the probability that it is not a lumen region 41, the probability that it is a biological tissue region 43, the probability that it is not a biological tissue region 43, and the like.

[0058] Fig. 5 is a flowchart explaining the flow of the program processing. Note that, prior to execution of the program in Fig. 5, the user specifies the 3D scan ID related to the three-dimensional scan to be processed and the smoothed object for which the center of gravity 67 is to be calculated.

[0059] The control unit 21 extracts a record to be processed from the control unit 21. The control unit 21 acquires the transverse cross-sectional image 58 recorded in the tomographic image field (step S501). The control unit 21 inputs the acquired transverse cross-sectional image 58 to the classification model 31, and acquires the classification data 57 to be output (step S502). The control unit 21 records the classification data 57 in the classification data field of the record from which the transverse cross-sectional image 58 was acquired (step S503).

[0060] The control unit 21 determines whether or not the processing of the set of transverse cross-sectional images 58 has been completed (step S504). If it is determined that the processing has not been completed (NO in step S504), the control unit 21 returns to step S501.

[0061] If it is determined that the process is completed (YES in step S504), the control unit 21 constructs a three-dimensional model based on the set of classification data 57 (step S505). The control unit 21 performs spatial smoothing processing on the three-dimensional model (step S506). As a result, the three-dimensional image 51 is completed.

[0062] The control unit 21 creates smoothed classified data 571 by cutting the three-dimensional image 51 at positions corresponding to each of the classified data 57 acquired in step S501. The control unit 21 calculates the center of gravity 67 for each of the smoothed classified data 571 (step S507).

[0063] The control unit 21 determines a center line 68 that connects the center points 67 calculated for each of the smoothed classification data 571 (step S508). Specifically, the control unit 21 interpolates between the center points 67 using an interpolation method such as linear interpolation, spline interpolation, or Lagrange interpolation.

[0064] The control unit 21 selects one center of gravity 67 (step S509). The control unit 21 determines an evaluation plane that passes through the selected center of gravity 67 and is perpendicular to the center of gravity line 68 (step S510). The control unit 21 calculates a representative value of the object based on the corrected classification data 54, which is a cross-sectional view of the three-dimensional image 51 cut by the evaluation plane (step S511).

[0065] The control unit 21 determines whether or not the processing of the center of gravity 67 included in the three-dimensional image 51 has been completed (step S512). If it is determined that the processing has not been completed (NO in step S512), the control unit 21 returns to step S509. If it is determined that the processing has been completed (YES in step S512), the control unit 21 displays the representative value (step S513). A specific example of the display will be described later. The control unit 21 ends the processing.

[0066] FIG. 6 is an example of the display. FIG. 6 shows an example in which the area of ​​the smoothed lumen region 411 is used as the representative value of each corrected classification data 54. A graph showing the change in area of ​​the smoothed lumen region 411 is displayed on the screen. The horizontal axis indicates the position of the transverse layer image 58 along the centroid line 68, i.e., the longitudinal direction of the blood vessel 15. The origin of the horizontal axis, i.e., the first axis, is the position of the centroid point 67 corresponding to the first transverse layer image 58 in the three-dimensional scan. The position of the horizontal axis is shown as the length from the origin along the longitudinal direction of the blood vessel 15. The unit of the horizontal axis is millimeters.

[0067] The vertical axis of the graph shown in FIG. 6, i.e., the second axis perpendicular to the first axis, is the area of ​​the smoothed lumen region 411 in the corrected classification data 54 passing through the center of gravity of each cross-sectional image 58. To improve the user's visibility, in FIG. 6, the word "after smoothing" is omitted and "lumen region area" is displayed next to the vertical axis. The unit of the vertical axis is square millimeters. The area of ​​the smoothed lumen region 411 in the corrected classification data 54 is an example of a representative value of an object in a plane that passes through the intersection of the cross-sectional image 58 and the center of gravity line 68 and is perpendicular to the center of gravity line 68.

[0068] In the graph shown in Fig. 6, MLA (Minimal Lumen Area) indicates the minimum value of the area of ​​the smoothed lumen region 411. In Fig. 6, a white circle is displayed at a position on the graph corresponding to the MLA, and the MLA value is displayed in the upper right corner of the screen. The MLA is an example of a representative value for the entire three-dimensional image 51.

[0069] 6, the MLA calculated based on the smoothed classification data 571 is shown in parentheses to the right of the MLA calculated based on the area of ​​the smoothed lumen region 411 in the corrected classification data 54 perpendicular to the center of gravity line 68. The smoothed classification data 571 is oblique to the blood vessel 15, and therefore has a larger value than the smoothed lumen region 411 in the corrected classification data 54. By displaying both MLAs, the user can grasp the patient's condition by utilizing their experience using a conventional information processing device 20 that does not use the corrected classification data 54.

[0070] The area of ​​the lumen region 41 calculated using an evaluation plane perpendicular to the center line 68 is displayed, allowing the user to appropriately select, for example, the size of the stent to be used, or the size of the expansion balloon, etc.

[0071] The representative value of corrected classification data 54 is not limited to the area of ​​smoothed lumen region 411. For example, any parameter such as the average diameter of smoothed lumen region 411, the thickness of the calcified region, the angle of the calcified region, or the stenosis rate can be used as the representative value. When an angle is used as the representative value of corrected classification data 54, it is desirable to use an angle based on the intersection of corrected classification data 54 and center of gravity line 68.

[0072] The control unit 21 may display the area of ​​the combined lumen region 49 in the classification data 57 on the screen shown in Fig. 6. It is possible to provide an information processing device 20 that displays a representative value that is not affected by the smoothing process when creating the three-dimensional image 51.

[0073] The representative value for the entire three-dimensional image 51 is not limited to MLA. For example, the length of a stenosis where the area of ​​the smoothed lumen region 411 is equal to or less than a reference value, or the length of a portion where a calcified region exists, can be used as the representative value. When using a length as a representative value for the entire three-dimensional image 51, it is preferable to use the length along the center of gravity line 68.

[0074] According to the present embodiment, it is possible to provide an information processing device 20 that outputs a representative value in a cross section perpendicular to the blood vessel 15. Even in a case where the image acquisition catheter 16 cannot be arranged parallel to the blood vessel 15, it is possible to provide an information processing device 20 that accurately outputs a representative value related to the blood vessel 15.

[0075] [Embodiment 2] This embodiment relates to an information processing device 20 that divides a blood vessel 15 into a plurality of segments 52 (see FIG. 15) based on the positional relationship between the blood vessel 15 and an image acquisition catheter 16. Descriptions of parts common to the first embodiment will be omitted.

[0076] Fig. 7 is an explanatory diagram for explaining a blood vessel 15 according to the second embodiment. Fig. 7 shows a schematic longitudinal section of a blood vessel 15 bent in the middle and having an imaging catheter 16 inserted therein. In Fig. 7, the left side is the tip side of the imaging catheter 16, and the right side is the base end side of the imaging catheter 16.

[0077] During three-dimensional scanning, the diagnostic device captures transverse slice images 58 while pulling back the sensor provided on the imaging catheter 16 to the right. Therefore, in one three-dimensional scan, transverse slice images 58 perpendicular to the imaging catheter 16 are captured in order from the left side.

[0078] 7, where the blood vessel 15 is bent, the radius of curvature of the imaging catheter 16 is larger than the radius of curvature of the blood vessel 15. The relationship between the blood vessel 15 and the imaging catheter 16 will be described by dividing it into three regions, type A, type B, and type C. Types A to C are examples of attributes of the segment 52.

[0079] In the type A region, as the three-dimensional scanning progresses, the imaging catheter 16 moves away from the center of gravity of the blood vessel 15. In the type B region, there is little change in the positional relationship between the center of gravity of the blood vessel 15 and the imaging catheter 16. In the type C region, as the three-dimensional scanning progresses, the imaging catheter 16 moves closer to the center of gravity of the blood vessel 15.

[0080] Fig. 8 is an explanatory diagram showing a schematic longitudinal section of a three-dimensional image 51 constructed by the three-dimensional scanning shown in Fig. 7. As described above, the smoothed catheter region 441 extends straight in the longitudinal direction along the central axis of the three-dimensional image 51. The smoothed biological tissue region 431 is depicted as bending more gently than the actual blood vessel 15.

[0081] 9 is an explanatory diagram illustrating the center-to-center distance W. In the smoothed classification image obtained by imaging the smoothed classification data 571, the distance between the center of the smoothed catheter region 441 and the center of gravity 67 of the smoothed connecting lumen region 491 is referred to as the center-to-center distance W. Note that the center of gravity 67 may be, for example, the smoothed biological tissue region 431 or the center of gravity of the inner surface of the smoothed biological tissue region 431.

[0082] 10 is an example of a graph showing the relationship between the acquisition position of the transverse image 58 and the center-to-center distance W. The horizontal axis indicates the position at which each transverse image 58 was taken, and is shown as the distance from the first transverse image 58 in the three-dimensional scan. The horizontal axis is in millimeters. The vertical axis indicates the center-to-center distance W of each transverse image 58, also in millimeters. The graph shown in FIG. 10 shows the change in the positional relationship between the center line 68 and the center line of the imaging catheter 16 along the longitudinal direction of the blood vessel 15.

[0083] The downward arrows shown in the graph indicate the positions where the center-to-center distance W is maximum or minimum. The vertical dashed lines indicate the boundaries of the segments 52 determined based on the fluctuation state of the center-to-center distance W. A1 to A9 indicate the symbols given to each of the downward arrows. R1 to R6 indicate the symbols given to each of the segments 52. In the following description, when it is necessary to distinguish between the segments 52 R1 to R6, they will be described as segment 52R1, segment 52R2, etc.

[0084] An example of a rule for dividing a segment 52 will be described. For each downward arrow shown in FIG. 10, if the difference in height between the downward arrow adjacent to either the left or right is equal to or greater than a threshold, the control unit 21 determines that it is the boundary of a segment 52. If the difference in height between the downward arrow adjacent to either the left or right is less than the threshold, the control unit 21 determines that it is not the boundary of a segment 52. For a downward arrow at the left end or the right end, the control unit 21 determines whether it is the boundary of a segment 52 based on the difference in height between the arrow and an adjacent downward arrow. The threshold for determining the boundary of a segment 52 is determined as appropriate, for example, depending on the part or thickness of the blood vessel 15.

[0085] A specific example will be given. The control unit 21 determines that the arrow A1 is the boundary of the segment 52 because the difference in height between the arrow A1 and the adjacent arrow A2 is equal to or greater than the threshold. The control unit 21 determines that the arrow A2 is the boundary of the segment 52 because the difference in height between the arrow A1 and the adjacent arrow A2 is equal to or greater than the threshold. The control unit 21 determines that the arrow A3 is not the boundary of the segment 52 because the differences in height between the arrow A3 and the adjacent arrows A2 and A4 are both less than the threshold. The control unit 21 determines that the arrow A4 is the boundary of the segment 52 because the difference in height between the arrow A4 and the adjacent arrow A5 is equal to or greater than the threshold. The control unit 21 determines whether the arrows A5 and onward are the boundary of the segment 52 using the same rule.

[0086] Note that the user may subjectively determine whether each downward arrow is a boundary of segment 52. The boundary of segment 52 may be determined based on the user's subjective determination regardless of the position of maximum or minimum of center-to-center distance W. Control unit 21 receives an instruction from the user, records the boundary of segment 52, and uses it for subsequent processing.

[0087] The control unit 21 classifies each of the divided segments 52 into types A to C described using Fig. 7 based on the relationship between the center of gravity of the blood vessel 15 at both ends of the segment 52 and the image acquisition catheter 16. In the example shown in Fig. 10, the control unit 21 classifies segments 52R3 and 52R5 into type B because the difference between the center-to-center distances W at both ends is less than the threshold. The threshold for determining whether or not to classify into type B is appropriately determined depending on, for example, the part or thickness of the blood vessel 15.

[0088] The control unit 21 classifies the segments 52 that are not determined to be type B into type A or type C. The control unit 21 classifies the segments 52R2 and 52R6 into type A because the center-to-center distance W is larger on the base end side of the image acquisition catheter 16 than on the tip end side. The control unit 21 classifies the segments 52R1 and 52R4 into type C because the center-to-center distance W is larger on the tip end side of the image acquisition catheter 16 than on the base end side.

[0089] For the type B segment 52, the image acquisition catheter 16 and the blood vessel 15 are approximately parallel, so there is no significant difference between the representative value calculated based on the classification data 57 and the representative value calculated based on the corrected classification data 54. Therefore, the representative value can be calculated based on the classification data 57 without using the procedure described using FIG.

[0090] For type A and type B segments 52, the imaging catheter 16 and the blood vessel 15 are not parallel. Therefore, it is desirable to calculate the representative values ​​based on the corrected classification data 54 using the procedure used in FIG.

[0091] 11 is a flow chart for explaining the processing flow of the program of the second embodiment. The control unit 21 starts a tomographic image processing subroutine (step S521). The tomographic image processing subroutine is a subroutine for calculating the center of gravity 67 and the center-to-center distance W at the position of each transverse cross-sectional image 58 based on a set of transverse cross-sectional images 58. The processing flow of the tomographic image processing subroutine will be described later.

[0092] The control unit 21 starts a segment division subroutine (step S522). The segment division subroutine is a subroutine for dividing a set of classified images into segments 52. The processing flow of the segment division subroutine will be described later.

[0093] The control unit 21 accepts the user's designation of the representative value calculation position (step S523). The user designates the representative value calculation position, for example, by selecting one cross-sectional image 58. The control unit 21 determines the cross-sectional image 58 and the classification data 57 corresponding to the designated position.

[0094] The control unit 21 determines which segment 52 the designated position is included in (step S524). The control unit 21 starts a type determination subroutine (step S525). The type determination subroutine is a subroutine that determines which type the target segment 52 is, from type A to type C described with reference to Fig. 7. The processing flow of the type determination subroutine will be described later.

[0095] The control unit 21 determines whether the segment 52 including the cross-sectional image 58 designated in step S523 is type B (step S526). If it is determined to be type B (YES in step S526), ​​the control unit 21 calculates a representative value based on the smoothed classification data 571 at the position designated in step S523 (step S527).

[0096] When it is determined that the image is not type B (NO in step S526), ​​the control unit 21 determines a center line 68 based on the center point 67 calculated in the tomographic image processing subroutine started in step S521 (step S533). The control unit 21 determines an evaluation plane that passes through the center point 67 of the smoothed classification data 571 corresponding to the position accepted in step S523 and is perpendicular to the center line 68 (step S534). The control unit 21 calculates a representative value based on the corrected classification data 54 obtained by cutting the three-dimensional image 51 constructed in step S531 with the evaluation plane (step S535).

[0097] After step S527 or step S535 is completed, the control unit 21 displays the representative value (step S528). The control unit 21 ends the process. The control unit 21 may calculate and display a representative value related to the segment 52, such as the minimum vascular lumen cross-sectional area of ​​the segment 52 determined in step S524.

[0098] Before executing step S533, the control unit 21 may recreate the three-dimensional image 51 based on the classification data 57 included in the segment 52 determined in step S524. It is possible to provide an information processing device 20 that calculates a representative value that is less susceptible to the effects of artifacts caused by bending of blood vessels.

[0099] 12 is a flowchart illustrating the flow of processing of the tomographic image processing subroutine, which is a subroutine for calculating the center of gravity 67 and the center distance W at the position of each transverse cross-sectional image 58 based on a set of transverse cross-sectional images 58.

[0100] The control unit 21 extracts a record to be processed from the control unit 21. The control unit 21 acquires the transverse cross-sectional image 58 recorded in the tomographic image field (step S541). The control unit 21 inputs the acquired transverse cross-sectional image 58 to the classification model 31, and acquires the classification data 57 to be output (step S542). The control unit 21 records the classification data 57 in the classification data field of the record from which the transverse cross-sectional image 58 was acquired (step S543).

[0101] The control unit 21 determines whether the processing of the set of cross-sectional images 58 has been completed (step S544). If it is determined that the processing has not been completed (NO in step S544), the control unit 21 returns to step S541. If it is determined that the processing has been completed (YES in step S544), the control unit 21 constructs a three-dimensional model based on the set of classification data 57 (step S545). The control unit 21 performs spatial smoothing processing on the three-dimensional model (step S546). With the above steps, the three-dimensional image 51 is completed.

[0102] The control unit 21 creates smoothed classification data 571 by cutting the three-dimensional image 51 at a position corresponding to the transverse cross-sectional image 58 acquired in step S541 (step S547). The control unit 21 calculates the center of gravity 67 of the specified object (step S548). The control unit 21 calculates the center-to-center distance W, which is the distance between the center of the catheter region 44 and the center of gravity 67 (step S549).

[0103] The control unit 21 records the calculated center of gravity 67 and center-to-center distance W in the main storage device 22 or the auxiliary storage device 23. Note that the tomographic image DB 36 may be provided with a field for recording an object and the center of gravity 67 and center-to-center distance W related to the object.

[0104] The control unit 21 determines whether or not the processing of the smoothed classification data 571 corresponding to the set of cross-sectional images 58 has been completed (step S590). If it is determined that the processing has not been completed (NO in step S590), the control unit 21 returns to step S547. If it is determined that the processing has been completed (YES in step S590), the control unit 21 ends the processing.

[0105] 13 is a flow chart for explaining the process flow of the segment division subroutine. The segment division subroutine is a subroutine for dividing a set of cross-sectional images 58 into segments 52.

[0106] The control unit 21 extracts the maximum and minimum points of the graph described with reference to Fig. 10 (step S551). Specifically, the control unit 21 extracts the transverse cross-sectional image 58 in which the sign of the difference obtained by subtracting the center-to-center distance W corresponding to the position of the next transverse cross-sectional image 58 from the center-to-center distance W corresponding to the position of the transverse cross-sectional image 58 to be processed is inverted. In the following description, the maximum and minimum points are collectively referred to as maximum and minimum points.

[0107] The control unit 21 selects one of the maximum and minimum points extracted in step S551 (step S552). The control unit 21 determines whether the difference between the maximum and minimum point selected in step S552 and at least one of the adjacent maximum and minimum points is equal to or greater than a threshold (step S553).

[0108] If it is determined that the difference is equal to or greater than the threshold (YES in step S553), the control unit 21 determines that the local maximum or minimum point being processed is a boundary between segments 52 (step S554). If it is determined that the difference is not equal to or greater than the threshold (NO in step S553), the control unit 21 determines that the local maximum or minimum point being processed is not a boundary between segments 52 (step S555).

[0109] After step S554 or step S555 is completed, the control unit 21 judges whether or not the processing of the maximum and minimum points extracted in step S551 is completed (step S556). If it is determined that the processing is not to be completed (NO in step S556), the control unit 21 returns to step S552. If it is determined that the processing is to be completed (YES in step S556), the control unit 21 terminates the processing.

[0110] By the segment division subroutine, the control unit 21 executes a process of dividing the blood vessel 15 into a plurality of segments 52 along the longitudinal direction.

[0111] 14 is a flowchart illustrating the flow of processing of a type determination subroutine. The type determination subroutine is a subroutine for determining which type the target segment 52 is, from type A to type C described with reference to FIG.

[0112] The control unit 21 determines whether the difference between the center distances W of both ends of the segment 52 to be processed is equal to or less than a threshold value (step S561). If it is determined that the difference is equal to or less than the threshold value (YES in step S561), the control unit 21 determines that the segment 52 being processed is type B (step S562).

[0113] If it is determined that the distance is not less than the threshold (NO in step S561), the control unit 21 determines whether the center-to-center distance W on the start point side of the segment 52 being processed, i.e., the tip side of the image acquisition catheter 16, is smaller than the center-to-center distance W on the end point side, i.e., the base end side of the image acquisition catheter 16 (step S563).If it is determined that the distance is smaller (YES in step S563), the control unit 21 determines that the segment 52 being processed is type A (step S564).

[0114] If it is determined that the size is not smaller (NO in step S563), control unit 21 determines that segment 52 being processed is type C (step S565). After step S562, step S564, or step S565 ends, control unit 21 ends the process.

[0115] According to this embodiment, in the case of type B segments 52, a representative value is calculated based on smoothed classification data 571, so that a method of calculating a representative value with a light processing load on information processing device 20 can be provided.

[0116] [Embodiment 3] This embodiment relates to an information processing device 20 that constructs a three-dimensional image 51 of a blood vessel 15 by three-dimensionally connecting segments 52 with each other. Description of parts common to the second embodiment will be omitted.

[0117] 15 is an explanatory diagram for explaining a method of connecting segments 52. A first segment 521 and a second segment 522 that is one segment closer to the base end than the first segment 521 will be explained as an example. Both the first segment 521 and the second segment 522 are shown as being cylindrical. Each segment 52 has a blood vessel 15 along its central axis. The blood vessel 15 is divided by the boundary of the segment 52.

[0118] The first segment 521 and the second segment 522 overlap in an overlap region 531. A gap region 532 exists between the first segment 521 and the second segment 522. The control unit 21 determines an angle between the first segment 521 and the second segment 522 so that a difference between the first segment 521 and the second segment 522 in the overlap region 531 is reduced. The control unit 21 combines the first segment 521 and the second segment 522 in the overlap region 531. The control unit 21 interpolates the gap region 532 by, for example, spline interpolation.

[0119] By repeating the above process to connect the segments 52, the control unit 21 can appropriately construct a three-dimensional image 51 of the entire three-dimensional scanning range. The control unit 21 can calculate feature amounts based on the constructed three-dimensional image 51.

[0120] 16 is a flow chart for explaining the processing flow of the program of the third embodiment. The control unit 21 starts a tomographic image processing subroutine (step S521). The tomographic image processing subroutine is a subroutine for calculating the center of gravity 67 and the center-to-center distance W at the position of each transverse cross-sectional image 58 based on a set of transverse cross-sectional images 58. The processing flow of the tomographic image processing subroutine is the same as the processing flow of the subroutine explained using FIG. 12.

[0121] The control unit 21 starts a segment division subroutine (step S522). The segment division subroutine is a subroutine that divides a set of classified images into segments 52. The process flow of the segment division subroutine is the same as the process flow of the subroutine described using FIG.

[0122] The control unit 21 constructs a three-dimensional image 51 of each segment using the smoothed classification data 571 included in each segment 52 (step S571). The control unit 21 connects the segments 52 to each other in an overlapping region 531 formed between adjacent segments 52 so as to reduce the difference between the overlapping segments 52 (step S572). The control unit 21 combines the overlapping segments 52 in the overlapping region 531. The control unit 21 interpolates the gap region 532 (step S573). In this way, a three-dimensional image 51 of the entire three-dimensional scanning range is constructed.

[0123] The control unit 21 performs a smoothing process on the constructed three-dimensional image 51, and smoothes the connection between the three-dimensional image 51 constructed for each segment in step S571 and the region interpolated in step S573 (step S574). The control unit 21 determines a centroid line 68 that connects the centroid points 67 calculated for each smoothed classification data 571 included in the three-dimensional image 51 (step S575). The flow of the subsequent process is similar to the process of the program of the first embodiment described using FIG. 5, and therefore a description thereof will be omitted.

[0124] According to this embodiment, even when three-dimensional scanning is performed in a state where the blood vessel 15 and the image acquisition catheter 16 are bent, it is possible to realize an information processing device 20 that appropriately calculates a representative value.

[0125] [Embodiment 4] This embodiment relates to an information processing device 20 that reconstructs a three-dimensional image 51 with a straight center of gravity line 68. Descriptions of parts common to the first embodiment will be omitted.

[0126] Fig. 17 is an explanatory diagram for explaining the three-dimensional image reconstruction procedure of the embodiment 4. As explained using Fig. 1, a center line 68 and an evaluation plane perpendicular to the center line 68 are defined inside the three-dimensional image 51. Corrected classification data 54, which is a cross-sectional view of the three-dimensional image 51 cut by the evaluation plane, is generated.

[0127] The procedure for reconstructing the corrected classification data 54 will be explained using the figures labeled (a) to (c) in Fig. 17 in order. (a) shows one corrected classification data 54 extracted for the purpose of explanation. The control unit 21 translates each evaluation plane in a direction perpendicular to the central axis of the three-dimensional image 51, i.e., the smoothed catheter region 441, so that the center points 67 are aligned in a straight line.

[0128] FIG. 1B shows the state after translation of corrected classification data 54 shown in FIG. 1A. In FIG. 1B, corrected classification data 54 before translation is shown by a two-dot chain line, and corrected classification data 54 after translation is shown by a solid line. In the following explanation, the straight center of gravity line 68 will be referred to as corrected center of gravity line 69.

[0129] Control unit 21 rotates corrected classification data 54 around center of gravity 67 so that corrected center of gravity line 69 is perpendicular to corrected classification data 54. (c) shows the state after corrected classification data 54 shown in (b) has been rotated. In (c), corrected classification data 54 before rotation is shown by a two-dot chain line, and corrected classification data 54 after rotation is shown by a solid line. Plane translation and rotation are well known, so detailed explanation will be omitted.

[0130] 17 shows a corrected three-dimensional image 511 constructed by translating and rotating each of the corrected classified data 54. The corrected classified data 54 are parallel to each other. In the following description, the direction of the corrected center of gravity line 69 may be referred to as a first direction.

[0131] The control unit 21 aligns, for example, the 0 o'clock direction of each corrected classification data 54 with a second direction perpendicular to the first direction, and arranges the corrected classification data 54 perpendicular to the corrected center of gravity line 69. The control unit 21 interpolates the smoothed intraluminal region 411, the smoothed biological tissue region 431, and the smoothed extraluminal region 451 to create a corrected three-dimensional image 511.

[0132] As a result of the above, a corrected three-dimensional image 511 is generated in which the corrected center of gravity line 69 is used in a first direction, and the corrected classification data 54, which is a cross-section of the three-dimensional image 51 in an evaluation plane that passes through the center of gravity point 67, which is the intersection of the transverse layer image 58 and the center of gravity line 68, and is perpendicular to the corrected center of gravity line 69, is arranged in a second direction perpendicular to the first direction.

[0133] The corrected three-dimensional image 511 simulates a state in which the blood vessel 15 is stretched straight, and is suitable for a user to check, for example, the state of contact between an implanted device such as a stent and the biological tissue region 43.

[0134] 18 is a flow chart for explaining the processing flow of the program of the fourth embodiment. The control unit 21 starts a tomographic image processing subroutine (step S521). The tomographic image processing subroutine is a subroutine for calculating the center of gravity 67 and the center-to-center distance W at the position of each transverse cross-sectional image 58 based on a set of transverse cross-sectional images 58. The processing flow of the tomographic image processing subroutine is the same as the processing flow of the subroutine explained using FIG. 12.

[0135] The control unit 21 determines a center line 68 that connects the center points 67 calculated in the tomographic image processing subroutine (step S508). The control unit 21 selects one center point 67 (step S509). The control unit 21 determines an evaluation plane that passes through the selected center point 67 and is perpendicular to the center line 68 (step S510).

[0136] The control unit 21 calculates the corrected classification data 54, which is a cross-sectional view obtained by cutting the three-dimensional image 51 constructed in the tomographic image processing subroutine with the evaluation plane determined in step S510 (step S581). The control unit 21 determines whether or not the processing of the center of gravity 67 included in the three-dimensional image 51 is completed (step S582). If it is determined that the processing is not completed (NO in step S582), the control unit 21 returns to step S509.

[0137] If it is determined that the process is completed (YES in step S582), the control unit 21 translates and rotates the corrected classification data 54 calculated in step S581 in accordance with the procedure described using (a) to (c) of Figure 17 (step S583).

[0138] The control unit 21 constructs a corrected three-dimensional image 511 based on the corrected classification data 54 moved in step S583 (step S584). In step S584, the three-dimensional image 51 is reconstructed into the corrected three-dimensional image 511. The control unit 21 displays the corrected three-dimensional image 511 on the display unit 25 in the form of, for example, a vertical cross section (step S585). The control unit 21 ends the process.

[0139] According to the present embodiment, it is possible to provide an information processing device 20 that generates and displays a corrected three-dimensional image 511 in a state in which the center of gravity line 68 is virtually stretched straight. It is possible to provide an information processing device 20 that allows a user to easily grasp the state of a stent, the shape of a calcified portion, or the spread of plaque.

[0140] [Embodiment 5] 19 is an explanatory diagram for explaining the configuration of an information processing device 20 according to the fifth embodiment. This embodiment relates to a form in which the information processing device 20 according to this embodiment is realized by combining and operating a general-purpose computer 90 and a program 97. Explanations of parts common to the first embodiment will be omitted.

[0141] The computer 90 includes a reading unit 29 in addition to the control unit 21, main memory device 22, auxiliary memory device 23, communication unit 24, display unit 25, input unit 26 and bus described above.

[0142] The program 97 is recorded in a portable recording medium 96. The control unit 21 reads the program 97 via the reading unit 29 and stores it in the auxiliary storage device 23. The control unit 21 may also read out the program 97 stored in a semiconductor memory 98 such as a flash memory implemented in the computer 90. Furthermore, the control unit 21 may download the program 97 from another server computer (not shown) connected via the communication unit 24 and a network (not shown), and store it in the auxiliary storage device 23.

[0143] The program 97 is installed as a control program of the computer 90, and is loaded into and executed by the main storage device 22. In this manner, the information processing device 20 described in the first embodiment is realized. The program 97 in this embodiment is an example of a program product.

[0144] A computer program can be deployed to be executed on a single computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0145] The technical features (constitutive elements) described in each embodiment can be combined with each other, and by combining them, new technical features can be formed. The embodiments disclosed herein are illustrative in all respects and should not be considered as limiting. The scope of the present invention is defined by the claims, not by the above meaning, and is intended to include all modifications within the scope and meaning equivalent to the claims.

[0146] Independent claims and dependent claims described in the claims may be combined with each other in any combination, regardless of the reference format. Furthermore, the claims may be written in a format in which a claim references two or more other claims (multiple claim format), but this is not limited to this format. The claims may also be written in a format in which a multiple claim references at least one other claim (multiple multiple claim format). [Explanation of symbols]

[0147] 15 Blood vessels 16 Imaging Catheter 20 Information processing device 21 Control section 22 Main storage 23 Auxiliary storage device 24 Communications Department 25 Display section 26 Input section 29 Reading unit 31 Classification Models 36 Tomographic Image DB 41 Luminal area 411 Luminal area after smoothing 43 Biological Tissue Area 431 Smoothed biological tissue area 44 Catheter Area 441 Catheter area after smoothing 45 Extracavitary area 451 Extraluminal area after smoothing 49 Combined lumen area 491 Combined lumen area after smoothing 51 Three-dimensional image 511 3D image after correction 52 Segments 521 First Segment 522 Second Segment 531 Duplicate area 532 Gap Area 54 Corrected classification data 57 Classification Data 571 Smoothed Classification Data 58 Cross section image 67 Center of gravity 68 Center of gravity line 69 Center of gravity line after correction 90 Computer 96 Portable recording media 97 Program 98 Semiconductor Memory

Claims

1. acquiring a plurality of cross-sectional images of the blood vessel at different positions along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting one or more objects in each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; Based on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity, a representative value of the one or more objects on the plane is determined. A program that causes a computer to carry out processing.

2. The object includes a vessel lumen, an external elastic lamina, a vessel adventitia, or a stent. The program according to claim 1.

3. The three-dimensional shape is The object detected from each of the plurality of cross-sectional images is disposed at a position corresponding to the cross-sectional image; Smoothing the placed object Build by Processing The program according to claim 1.

4. The center of gravity line is Calculating a center of gravity of a smoothed object obtained by cutting the three-dimensional shape along a plane corresponding to the cross-sectional image; The center of gravity calculated on each of the planes corresponding to the plurality of cross-sectional images is determined so as to be connected. The program according to claim 3.

5. Calculating a distance between an intersection of the transverse cross-sectional image and the center of gravity line and a center of the catheter in each of the transverse cross-sectional images; Dividing the blood vessel into a plurality of segments along a length of the blood vessel based on the calculated distances. The program according to claim 1.

6. determining attributes of each of the divided segments based on a relationship between the center line and a center line of the catheter; Based on the determined attribute, a representative value of the object in the cross-sectional view is determined, or a representative value of the object in the cross-sectional view is determined. The program according to claim 5.

7. constructing a solid shape of the object for each of the segments; Interpolating the solid shape between adjacent segments The program according to claim 5.

8. Accepting a selection of one transverse cross-sectional image from the plurality of transverse cross-sectional images acquired; determining the segment in which the selected cross-sectional image is included; The cross-sectional images included in the determined segments are used to construct a three-dimensional shape of the object. The program according to claim 5.

9. A representative value of an object determined based on the cross-sectional view and a representative value of the object in the cross-sectional image are displayed in different manners. The program according to claim 1.

10. A graph is displayed using the position of the transverse cross-sectional image along the longitudinal direction of the blood vessel as a first axis, and using the representative value of the object on a plane that passes through the intersection of the transverse cross-sectional image and the centroid line and is perpendicular to the centroid line as a second axis perpendicular to the first axis. The program according to any one of claims 1 to 9.

11. The centroid line is used in a first direction, and cross sections of the blood vessel in a plane that passes through an intersection between the transverse slice image and the centroid line and is perpendicular to the centroid line are arranged in a second direction perpendicular to the first direction, to construct a three-dimensional shape of the blood vessel. The program according to any one of claims 1 to 9.

12. acquiring a plurality of cross-sectional images of the blood vessel along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting objects from each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; Based on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity, a representative value of the object on the plane is determined. An information processing method in which processing is performed by a computer.

13. An information processing device including a control unit, The control unit is acquiring a plurality of cross-sectional images of the blood vessel at different positions along a longitudinal direction of the blood vessel using a catheter inserted into the blood vessel; Detecting one or more objects in each of said cross-sectional images; constructing a three-dimensional shape of the object based on the object detected from each of the plurality of cross-sectional images; determining a center of gravity line of the three-dimensional shape of one of said objects; Based on a cross-sectional view obtained by cutting the three-dimensional shape of the object along a plane perpendicular to the center of gravity, a representative value of the one or more objects on the plane is determined. Information processing device.

Images