Abstract: Technique includes acquiring first contact data of first time, associated with first particle in first region; calculating first position data on particles in the first region at second time, and receiving second position data on particles in second region at the second time; detecting second particle being in contact with the first particle and in the first region at the first time and being in the first region at the second time; copying, when the first and second particles are in contact at the second time, displacement of the second particle from the first contact data to second contact data of the second time; detecting third particle being in the first or second region at the second time and in contact with the first particle; and copying, when the third particle is listed in the first contact data, displacement of the third particle to the second contact data therefrom.

Abstract: In a biological simulation apparatus, an operation unit represents a structure domain where tissues of a biological organ exist by a structure mesh model based on a Lagrange description and a fluid domain where fluid inside the biological organ exists by an ALE fluid mesh model based on an ALE description method. In a fluid-structure interaction simulation, the operation unit deforms the structure mesh model, and then deforms the ALE fluid mesh model so as to form no gap on a first interface between a domain where a site other than a certain site of the biological organ in the structure domain exists and the fluid domain or no overlap with the structure domain. The operation unit captures a position of a second interface between a domain where the certain site exists and the fluid domain by using the ALE fluid mesh model as a reference.

Abstract: A biological model creation apparatus sets a plurality of control points respectively corresponding to a plurality of target points set on a plurality of valve annuli of a specified heart, on a plurality of valve annuli in a mesh model of a heart. Then, the biological model creation apparatus determines the positions of the control points in the mesh model on the basis of a first and second evaluation value regarding the positions of the plurality of control points. The first evaluation value indicates a degree of matching to relative positions among target points belonging to the same valve annulus. The second evaluation value indicates a degree of matching to relative positions among target points belonging to different valve annuli. Then, the biological model creation apparatus deforms the mesh model such that the positions of the plurality of control points coincide with the positions of their corresponding target points.

Abstract: Technique includes acquiring first contact data of first time, associated with first particle in first region; calculating first position data on particles in the first region at second time, and receiving second position data on particles in second region at the second time; detecting second particle being in contact with the first particle and in the first region at the first time and being in the first region at the second time; copying, when the first and second particles are in contact at the second time, displacement of the second particle from the first contact data to second contact data of the second time; detecting third particle being in the first or second region at the second time and in contact with the first particle; and copying, when the third particle is listed in the first contact data, displacement of the third particle to the second contact data therefrom.

Abstract: A biological model generating apparatus establishes, for each of a plurality of nodes on a centerline of a blood vessel, based on blood vessel information, a first circle and a second circle on a plane cutting through the node and intersecting the centerline at a right angle. The first circle centers at the node and has a first radius obtained by adding a margin of error to the radius of the blood vessel. The second circle centers at the node and has a second radius obtained by subtracting the margin of error from the radius. Subsequently, the generating apparatus generates an implicit function defining a curved surface that intersects the plane cutting through each of the plurality of nodes, at the inner side of the first circle but the outer side of the second circle. Then, the generating apparatus generates a mesh model based on the defined curved surface.

Abstract: A biological model generating apparatus establishes, for each of a plurality of nodes on a centerline of a blood vessel, based on blood vessel information, a first circle and a second circle on a plane cutting through the node and intersecting the centerline at a right angle. The first circle centers at the node and has a first radius obtained by adding a margin of error to the radius of the blood vessel. The second circle centers at the node and has a second radius obtained by subtracting the margin of error from the radius. Subsequently, the generating apparatus generates an implicit function defining a curved surface that intersects the plane cutting through each of the plurality of nodes, at the inner side of the first circle but the outer side of the second circle. Then, the generating apparatus generates a mesh model based on the defined curved surface.

Abstract: A biological model creation apparatus sets a plurality of control points respectively corresponding to a plurality of target points set on a plurality of valve annuli of a specified heart, on a plurality of valve annuli in a mesh model of a heart. Then, the biological model creation apparatus determines the positions of the control points in the mesh model on the basis of a first and second evaluation value regarding the positions of the plurality of control points. The first evaluation value indicates a degree of matching to relative positions among target points belonging to the same valve annulus. The second evaluation value indicates a degree of matching to relative positions among target points belonging to different valve annuli. Then, the biological model creation apparatus deforms the mesh model such that the positions of the plurality of control points coincide with the positions of their corresponding target points.

Abstract: A shape data generation method includes: generating a target shape of transformation from plural tomographic images of an object; specifying, from among plural vertices of a first shape that is a reference shape of the object, plural first vertices, each first vertex of which satisfies a condition that a normal line of the first vertex passes through a point that is located on the target shape and is located on a boundary of the object in any one of the plural tomographic images; identifying, for each of the plural first vertices, a second vertex that internally divides a segment between the first vertex and the point; transforming the first shape so as to put each of the plural first vertices on a corresponding second vertex; setting a shape after the transforming to the first shape; and executing the first specifying and the subsequent processings a predetermined number of times.

Abstract: In a biological simulation apparatus, an operation unit represents a structure domain where tissues of a biological organ exist by a structure mesh model based on a Lagrange description method and a fluid domain where fluid inside the biological organ exists by an ALE fluid mesh model based on an ALE description method. In a fluid-structure interaction simulation, the operation unit deforms the structure mesh model, and then deforms the ALE fluid mesh model so as to form no gap on a first interface between a domain where a site other than a certain site of the biological organ in the structure domain exists and the fluid domain or no overlap with the structure domain. The operation unit captures a position of a second interface between a domain where the certain site exists and the fluid domain by using the ALE fluid mesh model as a reference.

Abstract: This shape data generation method include: setting an input shape that has a simple shape that has a same topology as the target shape for a target shape that is a shape of a transformation target identified from image data; identifying first vertices that satisfy a predetermined condition including a first condition that a normal line of a certain vertex of the plural vertices crosses with the target shape, among plural vertices of the input shape; transforming the input shape so that a first vertex is moved in a direction of a normal line of the first vertex by a first distance that is shorter than a distance up to the target shape; and performing the identifying and the transforming a predetermined number of times while changing the input shape after the transforming as the input shape to be processed.

Abstract: An information processing method includes: converting voxel data to node data in which a voxel, which has a brightness value that is outside a certain brightness value range, is set as a first node, and a voxel, which has a brightness value that is within the certain brightness value range, is set as a second node that has a capability to extract relating nodes based on a neighborhood relationship between voxels; performing, for each second node, a calculation processing to calculate an output value of a reaction-diffusion equation by using a value corresponding to a brightness value of the second node and values corresponding to brightness values of relating nodes extracted from the second node, a predetermined number of times; and determining a brightness value of each second node from the output value of the reaction-diffusion equation after performing the calculation processing the predetermined number of times.

Abstract: A shape data generation method relating to this invention includes: first generating first three-dimensional voxel data that represents a target object by using first tomographic images, in which a first region occupied by the target object is designated, among plural tomographic images; extracting, from the first tomographic images, brightness values of voxels included in the first region; second generating a function for calculating a probability that a voxel is included in the first region by using the extracted brightness values; calculating, for each voxel among voxels in a voxel space that includes the plural tomographic images, a probability by using a brightness value of the voxel and the function; and third generating second three-dimensional voxel data that represents the target object by using the first three-dimensional voxel data and probabilities calculated for the voxels in the voxel space.

Abstract: A mapping method includes; mapping first and second models, each represented by polygonal elements of meshes and including a same number of regions, to a first and a second spherical surfaces, respectively; approximating boundaries of the regions by curves and moving nodes based on the curve approximation; associating the nodes on the boundary of first sphere with points on the boundary of the second sphere; moving the nodes other than the nodes on the boundary by minimizing changes of shapes and areas of the polygonal elements under a constraint that the nodes on the boundary of the first sphere are placed at positions corresponding to the associated points on the second sphere; and calculating a point in the second model for each of the nodes in the first model, from the corresponding node after the movement on the first sphere and corresponding polygonal elements on the second sphere.

Abstract: A shape data generation method includes: identifying, from among a plural vertices of a first shape to be transformed, one or plural first vertices satisfying a predetermined condition including a condition that a normal line of a vertex to be processed crosses with a second shape that is a shape of a transformation target, which is identified from image data; transforming the first shape so as to move each of the one or plural identified first vertices a predetermined distance toward a corresponding normal direction of the identified first vertex; and storing data concerning the plural vertices of the transformed first shape after the identifying and the transforming are executed the predetermined number of times.

Abstract: A shape data generation method relating to this invention includes: first generating first three-dimensional voxel data that represents a target object by using first tomographic images, in which a first region occupied by the target object is designated, among plural tomographic images; extracting, from the first tomographic images, brightness values of voxels included in the first region; second generating a function for calculating a probability that a voxel is included in the first region by using the extracted brightness values; calculating, for each voxel among voxels in a voxel space that includes the plural tomographic images, a probability by using a brightness value of the voxel and the function; and third generating second three-dimensional voxel data that represents the target object by using the first three-dimensional voxel data and probabilities calculated for the voxels in the voxel space.

Abstract: An information processing method includes: converting voxel data to node data in which a voxel, which has a brightness value that is outside a certain brightness value range, is set as a first node, and a voxel, which has a brightness value that is within the certain brightness value range, is set as a second node that has a capability to extract relating nodes based on a neighborhood relationship between voxels; performing, for each second node, a calculation processing to calculate an output. value of a reaction-diffusion equation by using a value corresponding to a brightness value of the second node and values corresponding to brightness values of relating nodes extracted from the second node, a predetermined number of times; and determining a brightness value of each second node from the output value of the reaction-diffusion equation after performing the calculation processing the predetermined number of times.

Abstract: This shape data generation method include: setting an input shape that has a simple shape that has a same topology as the target shape for a target shape that is a shape of a transformation target identified from image data; identifying first vertices that satisfy a predetermined condition including a first condition that a normal line of a certain vertex of the plural vertices crosses with the target shape, among plural vertices of the input shape; transforming the input shape so that a first vertex is moved in a direction of a normal line of the first vertex by a first distance that is shorter than a distance up to the target shape; and performing the identifying and the transforming a predetermined number of times while changing the input shape after the transforming as the input shape to be processed.

Abstract: A shape data generation method includes: generating a target shape of transformation from plural tomographic images of an object; specifying, from among plural vertices of a first shape that is a reference shape of the object, plural first vertices, each first vertex of which satisfies a condition that a normal line of the first vertex passes through a point that is located on the target shape and is located on a boundary of the object in any one of the plural tomographic images; identifying, for each of the plural first vertices, a second vertex that internally divides a segment between the first vertex and the point; transforming the first shape so as to put each of the plural first vertices on a corresponding second vertex; setting a shape after the transforming to the first shape; and executing the first specifying and the subsequent processings a predetermined number of times.

Abstract: A mapping method includes; mapping first and second models, each represented by polygonal elements of meshes and including a same number of regions, to a first and a second spherical surfaces, respectively; approximating boundaries of the regions by curves and moving nodes based on the curve approximation; associating the nodes on the boundary of first sphere with points on the boundary of the second sphere; moving the nodes other than the nodes on the boundary by minimizing changes of shapes and areas of the polygonal elements under a constraint that the nodes on the boundary of the first sphere are placed at positions corresponding to the associated points on the second sphere; and calculating a point in the second model for each of the nodes in the first model, from the corresponding node after the movement on the first sphere and corresponding polygonal elements on the second sphere.

Abstract: A disclosed method is a shape data generation method including: identifying, from among a plural vertices of a first shape to be transformed, one or plural first vertices satisfying a predetermined condition including a condition that a normal line of a vertex to be processed crosses with a second shape that is a shape of a transformation target, which is identified from image data; transforming the first shape so as to move each of the one or plural identified first vertices a predetermined distance toward a corresponding normal direction of the identified first vertex; and storing data concerning the plural vertices of the transformed first shape after the identifying and the transforming are executed the predetermined number of times.