Source: https://patents.google.com/patent/JP5721225B2/en
Timestamp: 2019-10-20 15:26:57
Document Index: 200480044

Matched Legal Cases: ['art 102', 'art 103', 'art 104', 'art 105', 'art 106', 'art 107', 'art 108']

JP5721225B2 - Shape data generation method, program, and apparatus - Google Patents
Shape data generation method, program, and apparatus Download PDF
JP5721225B2
JP5721225B2 JP2011147078A JP2011147078A JP5721225B2 JP 5721225 B2 JP5721225 B2 JP 5721225B2 JP 2011147078 A JP2011147078 A JP 2011147078A JP 2011147078 A JP2011147078 A JP 2011147078A JP 5721225 B2 JP5721225 B2 JP 5721225B2
JP2011147078A
JP2013015945A (en
耕平 畠中
久田　俊明
俊明 久田
清了 杉浦
巧 鷲尾
岡田　純一
純一 岡田
良昌 門岡
尚 岩村
2011-07-01 Application filed by 富士通株式会社, 国立大学法人 東京大学, 国立大学法人 東京大学 filed Critical 富士通株式会社
2011-07-01 Priority to JP2011147078A priority Critical patent/JP5721225B2/en
2013-01-24 Publication of JP2013015945A publication Critical patent/JP2013015945A/en
2015-05-20 Publication of JP5721225B2 publication Critical patent/JP5721225B2/en
2031-07-01 Anticipated expiration legal-status Critical
The present technology relates to a shape data generation method, a program, and an apparatus.
In the medical field, simulators such as surgery simulators and organ simulators are used for decision of treatment policy, diagnosis, postoperative prediction, development of medicines and medical devices, and the like. In such a simulator simulation, 3D shape data of an organ is used, but it is often not easy to generate 3D shape data of an organ. This is because the organ is present inside the living body and cannot be visually observed or directly measured, and the shape of the organ is inherently complicated.
For example, the following two methods are known as methods for generating three-dimensional shape data of an organ. First, (1) a doctor or the like observes a tomographic image such as a CT (Computed Tomography) image or an MRI (Magnetic Resonance Imaging) image, determines the boundary of each part of the organ, and draws a boundary line. Then, (2) a method of obtaining the shape of each individual organ by preparing three-dimensional shape data of a standard organ in advance and deforming the shape.
However, the former method has a problem that it is difficult to determine the boundary when the tomographic image is unclear due to unevenness of the contrast agent or a surgical trace. In addition, doctors who have knowledge and experience have to draw boundaries on hundreds of tomographic images, resulting in a heavy work load.
The latter method is modified by associating the points in the standard shape with the points in the target shape. However, if the points to be associated are not set appropriately, the deformation is performed well. There is a problem that it is not.
The following methods exist for the latter method. Specifically, the predicted shape model is represented by a triangular patch and its apex, and for each triangular patch, the observation data is searched in the normal direction from the center of gravity position of the triangular patch. When the observation data is detected by the search, the predicted shape model is deformed by applying a force so that the center of gravity of the patch moves in the direction of the observation data. However, this technique has a problem that an unnatural shape occurs when the normals intersect.
JP 2002-329216 A JP 2010-61431 A
Fred L. Bookstein "Principal Warps: Thin-Plate Splines and the Decomposition of Deformation", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE.VOL. 11 NO. 6, PP. 567-585, JUNE 1989
Accordingly, an object of the present technology is to provide a technology for generating highly accurate three-dimensional shape data in one aspect.
In this shape data generation method, (A) from a shape data storage unit of a shape data generation device that stores data of a plurality of vertices of a target shape that is a shape to be deformed, a vertex that is focused on among the plurality of vertices of the target shape A first vertex that satisfies a predetermined condition including a condition that a normal line has an intersection with a target shape that is a shape of a deformation target specified by image data stored in the image data storage unit of the shape data generation device And (B) transforming the target shape so that the identified first vertex is moved by a predetermined distance in the direction of the normal to the identified first vertex, and Storing the data in the shape data storage unit, and (C) specifying the first vertex and deforming the vertex of the target shape a predetermined number of times, and processing the shape vertex data after processing. Living To execute a step of storing the output data storage unit of the device in the shape data generation apparatus.
High-precision three-dimensional shape data can be generated.
FIG. 1 is a functional block diagram of the shape data generation apparatus according to the present embodiment. FIG. 2 is a diagram showing a main processing flow. FIG. 3 is a diagram illustrating a processing flow of the primary deformation processing. FIG. 4 is a diagram for explaining TPS Warp. FIG. 5 is a diagram showing an example in which the primary deformation process is applied to the left ventricle. FIG. 6 is a diagram illustrating an example in which the primary deformation process is applied to the right ventricle. FIG. 7 is a diagram for explaining a problem when target landmarks are arranged in a target shape. FIG. 8 is a diagram for explaining the outline of the secondary deformation process. FIG. 9 is a diagram illustrating a processing flow of the secondary deformation processing. FIG. 10 is a diagram illustrating a process flow of the landmark setting process. FIG. 11 is a diagram illustrating a process flow of the boundary point search process. FIG. 12 is a diagram for explaining the relationship between the position of the vertex v and the luminance value. FIG. 13 is a diagram for explaining the relationship between the position of the vertex v and the luminance value. FIG. 14 is a diagram illustrating an example of a case where the search point penetrates the shape before deformation. FIG. 15 is a diagram illustrating an example of a case where the search point penetrates the shape before deformation. FIG. 16 is a diagram for explaining a boundary point search method. FIG. 17 is a diagram illustrating a shape after the secondary deformation and a target shape. FIG. 18 is a functional block diagram of a computer.
A functional block diagram of the shape data generating apparatus 1 according to the present embodiment is shown in FIG. In the example of FIG. 1, the shape data generation apparatus 1 includes a standard shape data storage unit 101, a primary deformation processing unit 102, an image data storage unit 103, a primary deformation data storage unit 104, and first landmark data. A storage unit 105, a landmark processing unit 106, a secondary deformation processing unit 107, a second landmark data storage unit 110, a secondary deformation data storage unit 111, and a display unit 112 are included. The landmark processing unit 106 includes a setting unit 108 and a boundary point search unit 109.
The primary deformation processing unit 102 performs primary deformation processing, which will be described later, using data stored in the standard shape data storage unit 101 and the image data storage unit 103, and the processing result is converted into the primary deformation data storage unit 104 and Stored in the first landmark data storage unit 105. The primary transformation processing unit 102 instructs the display unit 112 to display a screen for designating a landmark. The setting unit 108 performs a landmark setting process (to be described later) using data stored in the image data storage unit 103, the primary deformation data storage unit 104, and the first landmark data storage unit 105. 2 stored in the landmark data storage unit 110. The boundary point search unit 109 performs a boundary point search process to be described later using data stored in the image data storage unit 103, the primary deformation data storage unit 104, and the first landmark data storage unit 105. The secondary transformation processing unit 107 performs processing using the data stored in the image data storage unit 103, the primary transformation data storage unit 104, and the second landmark data storage unit 110, and the processing result is converted into the primary transformation data. The data is stored in the storage unit 104 or the secondary deformation data storage unit 111. In addition, the secondary deformation processing unit 107 instructs the display unit 112 to display data stored in the secondary deformation data storage unit 111. The display unit 112 displays data on a display device or the like in accordance with instructions from the primary deformation processing unit 102 and the secondary deformation processing unit 107.
The standard shape data storage unit 101 stores data of a standard shape of the heart (hereinafter referred to as a standard shape). More specifically, STL (Standard Triangulated Language) data including vertex information and vertex connection information is stored. However, the data format is not limited to the STL data format.
The image data storage unit 103 stores segment image data. The segment image data is obtained by performing a process of filling the inside of the boundary with different luminance values for each part on a CT image or the like of a specific patient's heart. By layering segment image data, three-dimensional data of a target shape, which is a shape that is a target of deformation, is obtained.
Next, the operation of the shape data generation apparatus 1 shown in FIG. 1 will be described with reference to FIGS. In the present embodiment, the deformation process is performed so that the standard shape approaches the target shape.
First, the primary deformation processing unit 102 performs primary deformation processing (FIG. 2: step S1). The primary deformation process will be described with reference to FIGS. In the primary deformation process, rough alignment between the standard shape and the target shape is performed.
First, the primary deformation processing unit 102 reads standard shape data from the standard shape data storage unit 101 and also reads segment image data from the image data storage unit 103. The primary transformation processing unit 102 instructs the display unit 112 to display a landmark setting screen including standard shape data and segment image data. The display unit 112 displays a landmark setting screen on the display device in response to an instruction from the primary deformation processing unit 102 (FIG. 3: step S11).
The user looks at the landmark setting screen displayed on the display device and roughly aligns the standard shape with the target shape. Specifically, (1) A source landmark is set at a predetermined portion in the standard shape. (2) A target landmark is set in a portion corresponding to the position where the source landmark is arranged in the target shape. The predetermined part is a characteristic part in the heart, for example, four annulus parts, apex part, bottom part of right ventricular fluid surface, myocardial boundary (for example, boundary between right ventricle and left ventricle), four The end face of the pulmonary vein, the superior vena cava and the inferior vena cava.
The primary deformation processing unit 102 receives the setting of the source landmark and the target landmark, and stores the data of the source landmark and the target landmark (for example, three-dimensional coordinates) in the first landmark data storage unit 105 ( Step S13).
Then, the primary deformation processing unit 102 performs processing for deforming the standard shape by a technique such as TSP Warp (Thin Plate Spline Warp) described later according to the landmark data stored in the first landmark data storage unit 105. (Step S15). Then, the primary deformation processing unit 102 stores the data of the shape after the primary deformation as the processing result in the primary deformation data storage unit 104. Then, the process returns to the original process.
The format of the data stored in the primary deformation data storage unit 104 is the same as the format of the data stored in the standard shape data storage unit 101. The source landmark used for the primary deformation process is handled as a fixed point in the secondary deformation process. That is, the source landmark used in the primary deformation process is not moved in the secondary deformation process, and the position is not shifted.
Here, TPSWarp will be described. As shown in FIG. 4, when a source landmark and a target landmark corresponding to the source landmark are given in TPSWarp, the source landmark is deformed so as to overlap the target landmark. For details of TPS Warp, see, for example, the matters described in Non-Patent Document 1.
FIG. 5 shows an example in which the primary deformation process described above is applied to the left ventricle. FIG. 5 shows a segment image, a target shape specified from the segment image, a standard shape, and a shape after primary deformation generated by the primary deformation processing. The points attached to the standard shape are source landmarks, and the points attached to the target shape are target landmarks. By using the standard shape and the target shape in which landmarks are set in this way and performing deformation processing by TPS Warp, it is possible to obtain data of the shape after the primary deformation.
FIG. 6 shows an example in which the primary deformation process described above is applied to the right ventricle. FIG. 6 shows a segment image, a target shape specified from the segment image, a standard shape, and a shape after primary deformation generated by the primary deformation processing. The points attached to the standard shape are source landmarks, and the points attached to the target shape are target landmarks. In the example of FIG. 6, the shape after the primary deformation is indicated by a mesh line 60 so that it can be easily compared with the target shape.
As described above, by performing rough alignment in advance according to the landmark setting received from the user, detailed deformation performed later can be performed more effectively.
Returning to the description of FIG. 2, the secondary deformation processing unit 107 performs the secondary deformation processing (step S3). The secondary deformation process will be described with reference to FIGS.
First, an outline of the secondary deformation process will be described. When performing deformation processing by TPS Warp, it is considered effective to set the target landmark on the normal line of the source landmark, considering that the organ is generally rounded. For example, as shown in FIG. 7, it is conceivable that the source landmark is arranged in the shape before the deformation, the target landmark is arranged at the intersection of the normal of the source landmark and the target shape, and the deformation processing by TPS Warp is performed. . However, as shown in FIG. 7, when a situation occurs where the normals intersect, an unnatural shape different from the target shape may occur in the deformed shape.
Therefore, in the secondary deformation process according to the present embodiment, as shown in FIG. 8, the target land is divided into the points that internally divide the line connecting the source landmarks arranged in the shape before the deformation and the intersection point. A mark is placed and a deformation process is performed by TPS Warp. Further, by repeatedly performing such deformation processing, the target shape is gradually approached. As a result, an unnatural shape is less likely to occur in the deformed shape, and the direction of the normal line is likely to face the portion that should originally be the target.
Details of the secondary deformation process will be described with reference to FIGS. 9 to 16. First, the secondary deformation processing unit 107 sets an initial value of a variable t for counting the number of deformations as t = 0 (FIG. 9: Step S21). Next, the secondary deformation processing unit 107 counts the number of deformations by incrementing the variable t to t = t + 1, and sets the initial value of the variable m to m = 0 (step S23). m is a variable for counting the number of processed vertices.
Then, the secondary transformation processing unit 107 increments the variable m to m = m + 1 (step S25), and instructs the landmark processing unit 106 to perform the landmark setting process. Then, the landmark processing unit 106 performs a landmark setting process (step S27). The landmark setting process will be described with reference to FIGS.
First, the setting unit 108 in the landmark processing unit 106, the data stored in the primary transformation data storing unit 104, a random one to identify the vertex v (FIG. 10: step S41). Then, the setting unit 108 stores the source landmark data (that is, the fixed point) stored in the first landmark data storage unit 105 and the source landmark data stored in the second landmark data storage unit 110. The Euclidean distance between the vertex v and each source landmark is calculated. Then, the setting unit 108 determines whether the smallest one of the calculated Euclidean distances between the vertex v and each source landmark is equal to or less than the threshold D (step S43). Step S43 is a process performed to arrange the vertices v evenly in the shape before the secondary deformation process. In step S43, it is determined whether or not the following expression is satisfied.
Here, d (v, v i ) represents the Euclidean distance between the point v and the point v i . v i is a fixed point (that is, a vertex whose data is stored as a source landmark in the first landmark data storage unit 105) or a source landmark (a vertex whose data is stored in the second landmark data storage unit 110) ).
When it is determined that the minimum Euclidean distance between the vertex v and each source landmark is equal to or less than the threshold D (step S43: Yes route), the process returns to the original process. On the other hand, when it is determined that the minimum Euclidean distance between the vertex v and each source landmark is larger than the threshold D (step S43: No route), the setting unit 108 searches the boundary point search unit 109 for a boundary point search. Instruct the execution of the process. Then, the boundary point search unit 109 performs boundary point search processing (step S45). The boundary point search process will be described with reference to FIGS.
First, the boundary point search unit 109 calculates a unit normal vector n (v) (FIG. 11: step S61). Here, n (v) is a unit normal vector with respect to the surface H at the vertex v (εH). The unit normal vector is a normal vector having a length of 1. Incidentally, H (⊂V) is a shaped surface which is specified by the data stored in the primary deformation data storage unit 10 4, V (⊂R 3) is a voxel space specified by the segment image data. R 3 represents a real space. Here, for simplification, the segment image data takes a binary value of 0 or 1, but may take a value other than 0 or 1, or take a multi-value of 2 or more. It may be. A voxel is an element of a grid image corresponding to a pixel that is an element of a rectangular image of 2D image data in 3D image data.
Further, the boundary point search unit 109 determines whether the vertex v exists inside the target shape (step S63). In step S63, it is determined whether or not the following expression is satisfied.
Here, the mapping f: V → R from the voxel space V to the real space R is defined as follows. By this mapping f, the elements of the segment image data included in the voxel space V are associated with the real number space R.
Here, I is the luminance value of the voxel including the point p (∈V).
The process of step S63 is demonstrated using FIG.12 and FIG.13. As shown in FIG. 12, when the luminance value f (v) of the voxel space corresponding to the vertex v is larger than 0, the vertex v exists inside the target shape. Therefore, the boundary point is searched in the direction from the inside to the outside of the target shape by setting the coefficient k to be incremented by 1 in the process of step S75 described later. On the other hand, as shown in FIG. 13, when the luminance value f (v) of the voxel space corresponding to the vertex v becomes 0, the vertex v exists outside the target shape. Therefore, the boundary point is searched in the direction from the outside to the inside of the target shape by setting the coefficient k to be decremented by 1 in the process of step S89 described later.
When it is determined that the vertex v exists inside the target shape (step S63: Yes route), the boundary point search unit 109 sets the coefficient k to k = 0 (step S65). Further, the boundary point search unit 109 sets a point for determining whether or not it is a boundary point (hereinafter referred to as a search point) as follows (step S67).
Then, the boundary point search unit 109 determines whether a search point exists in the voxel space specified by the tomographic image data (step S69). In step S69, it is determined whether the following expression is satisfied.
When it is determined that no search point exists in the voxel space specified by the tomographic image data (step S69: No route), the process returns to the original process. This is because the search point has reached the outside of the voxel space, so that it can be determined that the normal with respect to the vertex v and the target shape do not have an intersection.
On the other hand, when it is determined that a search point exists in the voxel space specified by the tomographic image data (step S69: Yes route), the boundary point search unit 109 determines whether the search point has penetrated the pre-deformation shape ( Step S71). In step S71, it is determined whether the following expression is satisfied.
Here, the mapping g: V → R 3 is defined as follows. This mapping g, the elements of the segment image data included in the voxel space V is associated with the real space R 3.
Note that the limit g | H of the mapping g is n (v).
The process of step S71 is demonstrated using FIG.14 and FIG.15. If the search point penetrates the pre-deformation shape before reaching the boundary point, there is a possibility that the search for the boundary point has not been performed properly. The case where the search point penetrates the pre-deformation shape before reaching the boundary point may be, for example, the case shown in FIG. 14 or the case shown in FIG. That is, there may be a case where no boundary point exists in the search direction depending on the degree of deformation of the target shape with respect to the shape before deformation. In any case, there is a possibility that the boundary point cannot be detected or the boundary point is detected at an inappropriate position. In step S71, the inner product of the normal vector for the vertex v and the normal vector for the search point is calculated, and the inner product is smaller than 0 (that is, the angle formed by the normal vector is larger than 90 degrees). In addition, it is determined that the search point has penetrated the shape before deformation.
Returning to the description of FIG. 11, when it is determined that the search point has penetrated the shape before deformation (step S <b> 71: Yes route), an appropriate boundary point cannot be detected, and the process returns to the original process. On the other hand, when it is determined that the search point does not penetrate the pre-deformation shape (step S71: No route), the boundary point search unit 109 displays the luminance value of the voxel space corresponding to the search point and the voxel corresponding to the vertex v. The brightness value of the space is compared to determine whether the brightness value has changed significantly (step S73). In step S73, it is determined whether the following expression is satisfied.
If it is determined that the luminance value has not changed significantly (step S73: No route), the boundary point search unit 109 increments the coefficient k to k = k + 1 (step S75), and the process of step S67. Return to.
In this way, as shown in FIG. 16, it is possible to determine whether a boundary point exists while moving the search point by one voxel from the vertex v in the normal direction.
On the other hand, when it is determined that the luminance value has changed significantly (step S73: Yes route), the boundary point search unit 109 sets the search point as a boundary point (step S77). In step S77, search point data (for example, the value of k) is stored in a storage device such as a main memory. Then, the process returns to the original process.
On the other hand, a process performed when it is determined in step S63 that the vertex v exists outside the target shape (step S63: No route) will be described. Since the processing in this case is only different in the search direction from the processing described above, the contents of the basic processing are as described above. That is, the process of step S79 is the same as the process of step S65, the process of step S81 is the same as the process of step S67, the process of step S83 is the same as the process of step S69, and the process of step S85 is the step. It is the same as the process of S71, and the process of step S87 is the same as the process of step S73. Therefore, a detailed description of the processing in steps S79 to S87 is omitted.
In step S89, the boundary point search unit 109 decrements the coefficient k to k = k−1 (step S89) and returns to the process in step S81. As a result, the search point is moved by one voxel in the normal direction from the outside to the inside of the target shape. Further, the process of step S91 is the same as the process of step S77.
By performing the processing as described above, it is possible to detect the intersection (that is, the boundary point) between the normal with respect to the vertex v and the target shape.
Returning to the description of FIG. 10, the setting unit 108 determines whether the boundary point search unit 109 has detected a boundary point (step S47). If it is determined that no boundary point has been detected (step S47: No route), the process returns to the original process in order to process the next vertex.
On the other hand, when it is determined that a boundary point has been detected (step S47: Yes route), the setting unit 108 sets the internal dividing point of the line segment connecting the vertex v and the boundary point v + kn (v) as the target landmark. (Step S49). Specifically, the target landmark is set at the following points.
Then, the setting unit 108 sets the vertex v as a source landmark (step S51). The setting unit 108 stores the set source landmark and target landmark data in the second landmark data storage unit 110. Then, the process returns to the original process.
By performing the processing as described above, it is possible to set the inner dividing point of the line segment connecting the vertex in the shape before deformation and the boundary point in the target shape as the target landmark.
Returning to the description of FIG. 9, the secondary transformation processing unit 107 determines whether m <N for the variable m (step S29). Here, N is the total number of vertices in the shape after the primary deformation (or the shape obtained by deforming the shape after the primary deformation). If it is determined that m <N (step S29: Yes route), the process returns to step S25 to process the next vertex.
On the other hand, when it is determined that m <N is not satisfied with respect to the variable m (step 29: No route), the secondary transformation processing unit 107 causes the source landmark and target land stored in the second landmark data storage unit 110 to be stored. In accordance with the mark data, deformation processing by TPS Warp is performed, and the deformed shape data is stored in the primary deformation data storage unit 104 (step S31). As described above, in the deformation process in step S31, the point that was the source landmark in the primary deformation process is handled as a fixed point and is not moved.
Then, the secondary deformation processing unit 107 determines whether t <T for the variable t (step S33). If it is determined that t <T (step S33: Yes route), the process returns to step S23 in order to perform further deformation processing. T is the total number of deformations, and is set in advance by an administrator or the like (for example, T = 500).
On the other hand, when it is not determined that t <T for the variable t (step S33: No route), since the deformation of T times is completed, the shape data after the secondary deformation process is stored in the secondary deformation data storage unit 111. Store and return to the original process.
By performing the processing as described above, the shape after the primary deformation approaches the target shape, and highly accurate three-dimensional shape data can be obtained. In addition, with such a modification method, the processing time can be relatively short.
Returning to the description of FIG. 2, when the secondary deformation process is performed, the display unit 112 displays the data stored in the secondary deformation data storage unit 111 on a display device or the like (step S5). Then, the process ends.
FIG. 17 shows an example of data displayed on a display device or the like. In the example of FIG. 17, a target shape and a shape after secondary deformation indicated by a mesh line are displayed. The figure on the left is a diagram showing the entire deformed part, and the figure on the right is an enlarged view of a part of the deformed part.
By performing the processing as described above, the standard shape of the heart is deformed so as to be close to the target shape specified by the segment image data, so that highly accurate three-dimensional shape data can be obtained. Become.
Although one embodiment of the present technology has been described above, the present technology is not limited to this. For example, the functional block diagram of the shape data generation apparatus 1 described above does not necessarily correspond to an actual program module configuration.
In the processing flow described above, the processing order can be changed if the processing result does not change. Further, it may be executed in parallel.
In the example described above, segment image data is displayed on the landmark setting screen to set the target landmark. However, for example, a target landmark may be set by displaying a tomographic image such as a CT image.
Further, the processing as described above is not only applicable to the heart but can also be applied to other objects.
The shape data generation device 1 described above is a computer device, and as shown in FIG. 18, a display control unit 2507 connected to a memory 2501, a CPU 2503, a hard disk drive (HDD) 2505, and a display device 2509. A drive device 2513 for the removable disk 2511, an input device 2515, and a communication control unit 2517 for connecting to a network are connected by a bus 2519. An operating system (OS) and an application program for executing the processing in this embodiment are stored in the HDD 2505, and are read from the HDD 2505 to the memory 2501 when executed by the CPU 2503. The CPU 2503 controls the display control unit 2507, the communication control unit 2517, and the drive device 2513 according to the processing content of the application program, and performs a predetermined operation. Further, data in the middle of processing is mainly stored in the memory 2501, but may be stored in the HDD 2505. In an embodiment of the present technology, an application program for performing the above-described processing is stored in a computer-readable removable disk 2511 and distributed, and installed from the drive device 2513 to the HDD 2505. In some cases, the HDD 2505 may be installed via a network such as the Internet and the communication control unit 2517. Such a computer apparatus realizes various functions as described above by organically cooperating hardware such as the CPU 2503 and the memory 2501 described above and programs such as the OS and application programs. .
Note that each processing unit illustrated in FIG. 1 may be realized by a combination of the CPU 2503 and the program, that is, the CPU 2503 executing the program. More specifically, the CPU 2503 may function as a processing unit as described above by performing an operation according to a program stored in the HDD 2505 or the memory 2501. Further, each data storage unit shown in FIG. 1 may be realized as the memory 2501 or the HDD 2505 in FIG.
The above-described embodiment can be summarized as follows.
Shape data generation method according to the present embodiment, from the shape data storage unit for storing data of the vertexes of the first shape to be (A) deformation of the vertices of the first shape, the law of the vertices focused A specifying step of specifying a first vertex satisfying a predetermined condition including a condition that the line has an intersection with the second shape specified by the tomographic image data stored in the image data storage unit; and (B) The first shape is deformed so that the first vertex is moved a predetermined distance in the direction of the normal line with respect to the first vertex, and the vertex data of the first shape after deformation is stored in the shape data storage unit And (C) storing the vertex data of the first shape deformed by executing the identifying step and the deforming step a predetermined number of times in the output data storage unit.
If the first shape is gradually deformed and brought closer to the second shape by such processing, an unnatural portion is hardly generated in the deformed shape so that highly accurate shape data can be generated. Become. Further, with such processing, shape data can be generated in a relatively short time.
The predetermined condition described above is, with a first vertex of the displacement have vertices that focuses may include a condition that is away more than a predetermined distance. In this way, since the part to be deformed is not biased, the deformed shape becomes smooth, and more accurate shape data can be generated.
In addition, the method described above includes (D) data stored in a standard shape data storage unit that stores data of vertices of standard shapes of the objects related to the first and second shapes, And (E) the start point overlaps the target point, and the step of receiving the specification of the start point in the standard shape and the specification of the target point corresponding to the start point in the second shape The standard shape may be deformed as described above, and the vertex data of the standard shape after the deformation may be stored in the shape data storage unit. In this way, the first shape can be brought close to the second shape in advance, so that later deformation can be performed more effectively.
Further, the predetermined condition described above may include a condition that the focused vertex is not included in the start point, and the deformation may be performed so that the start point is not moved in the deformation step. By fixing the position of the start point so that it does not deviate from the target point, it becomes possible to make the shape closer to the second shape.
Also, certain steps described above, (a1) the vertices focused by a predetermined distance in the direction of the normal of the vertex and the focus point of the move destination, included in the voxel space specified by the tomographic image data a determining step of determining either, (a2) if the point of destination is determined to be included in the voxel space, based on the inner product of a normal vector at a point on the destination and the normal vector of the vertex focused Determining whether the destination point has penetrated the first shape; and (a3) if it is determined that the destination point has not penetrated the first shape, the luminance value at the destination point A step of comparing the luminance value at the focused vertex and determining whether the luminance value has changed significantly; (a4) if it is determined that the luminance value has changed significantly, the normal to the focused vertex is the second Shape and intersection Determining that satisfy the condition that a, (a5) if a point of destination points or if the destination that has been determined not to be included in the voxel space is determined to pass through the first shape, focused A step of determining that the normal to the vertex does not satisfy the condition that it has an intersection with the second shape, and (a6) a step after the determination step when it is determined that the luminance value has not changed significantly. A step of re-executing the destination point may be included. In this way, it is possible to appropriately determine whether or not the normal for the focused vertex has an intersection with the second shape.
In addition, the object according to the first and second shapes is the heart, and the part where the start point and the target point are specified is the annulus, the apex, the bottom of the right ventricular fluid surface, the myocardial boundary, the pulmonary vein, It may be at least one of the vena cava and the inferior vena cava. If the positions of the characteristic portions in the heart are matched in advance, the shape can be made closer to the second shape.
A program for causing a computer to perform the processing according to the above method can be created. The program can be a computer-readable storage medium such as a flexible disk, a CD-ROM, a magneto-optical disk, a semiconductor memory, a hard disk, or the like. It is stored in a storage device. The intermediate processing result is temporarily stored in a storage device such as a main memory.
A shape data generation method according to the shape data generation apparatus,
From the shape data storage unit of the shape data generation apparatus that stores data of a plurality of vertices of a target shape that is a shape to be deformed, a normal line for the focused vertex among the plurality of vertices of the target shape is the shape Identifying a first vertex that satisfies a predetermined condition including a condition of having an intersection with a target shape that is a shape of a deformation target specified by image data stored in an image data storage unit of the data generation device;
Said first vertex which is specific to deform the object shape as the first to the distance moved in the normal direction of the first vertex of the data of the plurality of vertices of the object shape after deformation Storing in the shape data storage unit;
Storing the vertex data of the shape after the first vertex is specified and the target shape is deformed a predetermined number of times in an output data storage unit of the shape data generation device;
Hints, shape data generation method further executed in the shape data generation apparatus.
The shape data generation method includes:
The shape data generation method according to claim 1, wherein the predetermined condition further includes a condition that the focused vertex is at least a second distance away from any of the first vertices.
The shape data generation method further includes:
In the standard shape which is a standard shape specified by the vertex data stored in the standard shape data storage unit of the shape data generation device, the start point is specified, and the target point corresponding to the start point in the target shape is A step of accepting the designation;
Generating the target shape by deforming the standard shape so that the start point overlaps the target point, and storing data of a plurality of vertices of the target shape in the shape data storage unit;
The shape data generation method according to claim 1, wherein:
In the shape data generation method,
The predetermined condition includes a condition that the focused vertex is not included in the start point;
The shape data generation method according to claim 3, wherein in the step of deforming the vertex of the target shape, deformation is performed so as not to move the start point.
Identifying a first vertex that satisfies the predetermined condition,
Said interest vertex is moved a distance normal to the direction the third of vertices and the focused, a judgment step in which the point of destination to determine whether included in the voxel space specified by the image data,
When it is determined that the destination point is included in the voxel space, the destination point is determined based on an inner product of a normal vector for the focused vertex and a normal vector for the destination point. Determining whether the target shape has been penetrated;
When it is determined that the destination point does not penetrate the target shape, the luminance value at the destination point is compared with the luminance value at the focused vertex to determine whether the luminance value has changed When,
If it is judged that the SL luminance value changes, the condition is satisfied and determining that the normal of the vertex and the focus has said target shape and the intersection point,
When it is determined that the destination point is not included in the voxel space, or when it is determined that the destination point has penetrated the target shape, the normal of the focused vertex intersects with the target shape. Determining that the condition of having
When it is determined that the luminance value has not changed, the step after the determination step is re-executed for the destination point;
The shape data generation method according to claim 3 or 4 , comprising:
The object related to the target shape and the target shape is a heart,
The portion where the start point and the target point are specified is at least one of the annulus of the heart, the apex, the bottom of the right ventricular fluid surface, the myocardial boundary, the pulmonary vein, the superior vena cava and the inferior vena cava The shape data generation method according to any one of appendices 3 to 5, characterized in that:
A shape data generating program,
From the shape data storage unit that stores data of a plurality of vertices of the target shape that is the shape to be deformed, a normal line for the focused vertex among the plurality of vertices of the target shape is stored in the image data storage unit. Identifying a first vertex satisfying a predetermined condition including a condition of having an intersection with a target shape that is a shape of a deformation target specified by image data;
A shape data generation program characterized by causing a computer to execute.
A shape data storage unit that stores data of a plurality of vertices of a target shape that is a shape to be deformed;
An image data storage unit for storing image data;
An output data storage unit;
A predetermined condition including a condition that, from the shape data storage unit, a normal line of a target vertex among a plurality of vertices of the target shape has an intersection with a target shape that is a shape of a deformation target specified by the image data A specifying unit for specifying a first vertex satisfying the condition:
Said first vertex which is specific to deform the object shape as the first to the distance moved in the normal direction of the first vertex of the data of the plurality of vertices of the object shape after deformation stores the shape data storage unit, and a deformable portion for storing data of the vertexes of the shape after the specific and deformation of the object shape of the first vertex and a predetermined number of times of execution, the output data storage unit,
A shape data generating apparatus characterized by comprising:
DESCRIPTION OF SYMBOLS 1 Shape data generation apparatus 101 Standard shape data storage part 102 Primary deformation | transformation process part 103 Image data storage part 104 Primary deformation | transformation data storage part 105 1st landmark data storage part 106 Landmark process part 107 Secondary deformation | transformation process part 108 Setting 109 Boundary point search unit 110 Second landmark data storage unit 111 Secondary deformation data storage unit
A shape data generation method by a shape data generation device,
The target shape is deformed so as to move the identified first vertex in the direction of the normal to the first vertex, and data of a plurality of vertices of the modified target shape is Storing in the shape data storage unit;
A shape data generation method executed by the shape data generation apparatus.
Wherein the predetermined condition further shape data generation method according to claim 1, characterized in that it comprises a condition that the vertices that paying attention is distant second distance or more with any of the first vertex.
Wherein the predetermined condition comprises a condition that the vertices that paying attention is not included in the starting point after the movement,
In the process of deforming the object shape, without moving the vertex corresponding to the starting point after the movement of the plurality of vertices of the object shape, and the starting point after the movement of the plurality of vertices of the object shape The shape data generation method according to claim 3, wherein deformation is performed so as to move vertices other than the vertex corresponding to .
Paying attention to the third is the distance moved in the normal direction of the vertices to eyes wearing the apex, a judgment step in which the point of destination to determine whether included in the voxel space specified by the image data,
If the point of the destination is determined to be included in the voxel space, based on the inner product of a normal vector at a point on the normal vectors and the destination for said vertices and paying attention, the point of the destination Determining whether has penetrated the target shape;
If the point of the destination is determined not to penetrate the target shape is compared with the luminance value in the vertex and paying attention to the luminance value at the point of the destination, determines whether the brightness value changes Steps,
If the luminance value is determined to have changed, the condition is satisfied and determining that the normal of the said vertices and paying attention with the target shape and the intersection point,
If the point of the destination is determined as the point or if the destination that has been determined not to be included in the voxel space penetrates the target shape, the normal line of the apex were paying attention with the target shape Determining that the condition of having an intersection is not satisfied;
The shape data generation method according to claim 3 or 4, comprising:
A shape data generation program,
The target shape is deformed so as to move the identified first vertex in the direction of the normal to the first vertex, and data of a plurality of vertices of the modified target shape is A deforming unit for storing in the output data storing unit the data of the vertex of the shape after being stored in the shape data storage unit and executing the specified number of times of the first vertex and the deformation of the target shape a predetermined number of times;
JP2011147078A 2011-07-01 2011-07-01 Shape data generation method, program, and apparatus Active JP5721225B2 (en)
JP2011147078A JP5721225B2 (en) 2011-07-01 2011-07-01 Shape data generation method, program, and apparatus
US13/483,495 US9208617B2 (en) 2011-07-01 2012-05-30 Shape data generation method and apparatus
EP12170176.7A EP2541501A3 (en) 2011-07-01 2012-05-31 Shape data generation method and apparatus
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US9818200B2 (en) 2013-11-14 2017-11-14 Toshiba Medical Systems Corporation Apparatus and method for multi-atlas based segmentation of medical image data
US9193868B1 (en) 2014-05-06 2015-11-24 Sabic Global Technologies B.V. Article comprising poly(phenylene ether)-polysiloxane copolymer composition
EP3289017B1 (en) 2015-04-27 2019-02-27 SABIC Global Technologies B.V. Poly(phenylene ether) composition and article
US5444838A (en) * 1991-03-18 1995-08-22 Hewlett-Packard Company Computer system and method for interference checking of polyhedra using capping polygons
DE10111661A1 (en) 2001-03-09 2002-09-12 Philips Corp Intellectual Pty Image segmentation method for segmenting a selected region from a multi-dimensional dataset, uses a shape model representing the general outline of the region and sets up an adaptive mesh
EP1371013B1 (en) 2001-03-09 2017-04-12 Koninklijke Philips N.V. Image segmentation
WO2004110309A2 (en) * 2003-06-11 2004-12-23 Case Western Reserve University Computer-aided-design of skeletal implants
JP5017909B2 (en) * 2005-06-22 2012-09-05 コニカミノルタエムジー株式会社 Region extraction apparatus, region extraction method, and program
JP4969809B2 (en) * 2005-07-07 2012-07-04 東芝メディカルシステムズ株式会社 Ultrasonic diagnostic apparatus, image processing apparatus, and image processing method
JP2007312971A (en) * 2006-05-25 2007-12-06 Konica Minolta Medical & Graphic Inc Modeling apparatus, modeling method and program
ES2461353T3 (en) * 2008-05-15 2014-05-19 Intelect Medical Inc. Clinical programmer system and method to calculate activation volumes
JP4931022B2 (en) 2008-09-04 2012-05-16 独立行政法人産業技術総合研究所 Clothing state estimation method and program
JP5610129B2 (en) * 2010-03-26 2014-10-22 富士通株式会社 Three-dimensional template deformation method, apparatus and program
US8538737B2 (en) * 2010-09-17 2013-09-17 Adobe Systems Incorporated Curve editing with physical simulation of mass points and spring forces
US8669995B2 (en) * 2010-10-08 2014-03-11 Adobe Systems Incorporated Methods and apparatus for stroke grouping for high-level sketch editing
2011-07-01 JP JP2011147078A patent/JP5721225B2/en active Active
2012-05-30 US US13/483,495 patent/US9208617B2/en active Active
2012-05-31 EP EP12170176.7A patent/EP2541501A3/en active Pending
JP2013015945A (en) 2013-01-24
US20130002677A1 (en) 2013-01-03
EP2541501A3 (en) 2017-06-21
EP2541501A2 (en) 2013-01-02
US9208617B2 (en) 2015-12-08
CN102368972B (en) 2015-08-19 The use of patient-specific model of image-guided procedure computerized simulation system and method
US20070179377A1 (en) 2007-08-02 Elastic image registration
US9141763B2 (en) 2015-09-22 Method and system for patient-specific computational modeling and simulation for coupled hemodynamic analysis of cerebral vessels
Halier et al. 2000 Nondistorting flattening maps and the 3-D visualization of colon CT images
US20090285460A1 (en) 2009-11-19 Registration processing apparatus, registration method, and storage medium
EP3100236B1 (en) 2019-07-10 Method and system for constructing personalized avatars using a parameterized deformable mesh
US7496222B2 (en) 2009-02-24 Method to define the 3D oblique cross-section of anatomy at a specific angle and be able to easily modify multiple angles of display simultaneously
Zeng et al. 2010 Supine and prone colon registration using quasi-conformal mapping
Konrad-Verse et al. 2004 Virtual resection with a deformable cutting plane.
US8144949B2 (en) 2012-03-27 Method for segmentation of lesions
US20090180675A1 (en) 2009-07-16 System and method for image based multiple-modality cardiac image alignment
US8582856B2 (en) 2013-11-12 Image processing apparatus, image processing method, and program
Viceconti et al. 2007 The multimod application framework: a rapid application development tool for computer aided medicine
JP4170096B2 (en) 2008-10-22 The image processing apparatus for conformity assessment of a three-dimensional mesh model that is mapped onto the three-dimensional surface of the object
US7773786B2 (en) 2010-08-10 Method and apparatus for three-dimensional interactive tools for semi-automatic segmentation and editing of image objects
US8493389B2 (en) 2013-07-23 3D connected shadow mouse pointer
EP2369553B1 (en) 2018-10-24 Three-dimensional template transformation method and apparatus
KR20080110738A (en) 2008-12-19 Medical image display method and program thereof
JP3712234B2 (en) 2005-11-02 ROI extraction method and image processing server
JP2011125567A (en) 2011-06-30 Information processor, information processing method, information processing system and program
US20100293505A1 (en) 2010-11-18 Anatomy-related image-context-dependent applications for efficient diagnosis
WO2011074162A1 (en) 2011-06-23 Image processing apparatus, image processing method, image processing system, and program
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