Abstract: Based on heart behavior data, a computation unit determines a first time step at which a heart exhibits a first behavior in response to a first wave of an electrical signal, as well as a second time step at which the heart exhibits a second behavior in response to a second wave of the same. The computation unit reproduces the heart's behavior over time by updating a three-dimensional model of the heart according to the heart behavior data, simultaneously with variations in electrical signal strength over time according to electrocardiogram data. The computation unit coordinates this reproduction such that a first shape of the heart at the first time is reproduced step simultaneously with the first wave of the electrical signal, and such that a second shape of the heart at the second time step is reproduced simultaneously with the second wave of the electrical signal.

Abstract: A disclosed method includes extracting a region from each of plural cross sections in a volume data representing a solid to be rendered, based on data of brightness values of texels for each of the plurality of cross sections, wherein the plural cross sections are perpendicular to an axis set for the volume data; deleting any one of two adjacent cross sections among the plural cross sections based on a correlation between a region extracted for one cross section of the two adjacent cross sections and a region extracted for the other cross section of the two adjacent cross sections; and rendering the solid by using data of the cross sections after the deleting.

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 visualization apparatus includes a storage unit and a computation unit. The storage unit stores a three-dimensional model of a heart, excitation propagation data indicating temporal variations of electrical signal strength in myocardium during propagation of excitation in the heart, and infarct area data indicating locations of infarct areas in the heart. The computation unit places a measurement point on an accessory pathway between the infarct areas. Then based on the excitation propagation data, the computation unit determines a variation range of electrical signal strength as a range between its minimum and maximum values at the measurement point. The computation unit outputs a picture that visualizes propagation of cardiac excitation in the three-dimensional model, based on the excitation propagation data, by varying a visual property in the picture to represent variations of the electric signal strength within the determined variation range.

Abstract: A disclosed method includes: identifying an axis that is a straight or curved line inside of a space; first generating plural surface regions that are orthogonal to the identified axis; second generating, from a first vector provided at each vertex of an unstructured grid disposed inside of the space, a second vector at each point of plural points on a surface region for each of the generated plural surface regions; and displaying an arrow corresponding to the generated second vector.

Abstract: A computer sets a first point on a first part in a plurality of tomographic images of an organ. The computer determines a relative position of the first point with respect to reference positions of the first part and a second part in the tomographic images. The computer sets a second point in association with the first point, on the first part in a 3D model representing a structure of the organ, such that a relative position of the second point with respect to reference positions of the first part and the second part in the 3D model matches the relative position of the first point. Then, the computer deforms the 3D model such that, when the tomographic images and the 3D model are placed in the same coordinate system, the position of the second point matches that of the first point.

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: In this visualization method, for each brightness value for voxels included in a predetermined Region Of Interest (ROI) in a three-dimensional volume data, opacity is set according to an appearance frequency of the brightness value. Then, three-dimensional image data is generated for a portion on and under a cross section set for the three-dimensional volume data, by using color data that corresponds to a brightness value of each voxel included in the ROI and the opacity of each brightness value. Then, a cross section image generated from data of voxels on the cross section and the three-dimensional image data are superimposed and displayed.

Abstract: An apparatus for presuming positions of organs is configured to transform plural organs included in a template that is a model including the plural organs so as to match a predetermined target organ among the plural organs in the template to a corresponding organ in volume data; and perform a first processing and a second processing a predetermined number of times. The first processing includes transforming a first organ selected among the plural organs in the template according to a corresponding first organ in the volume data, and the second processing includes transforming, for each of second organs that are predetermined organs, which are influenced by transformation of the first organ, the second organ according to transformation performed for third organs that are predetermined organs, which influence the second organ in the template.

Abstract: A shape data generation apparatus includes a detection unit and a generation unit. With reference to model information indicating the thicknesses and the positions of both ends of a plurality of elements each having a cylindrical surface, the detection unit detects a connection point where two or more elements are connected to each other, on the basis of the positions of both ends of the elements. The generation unit generates a curved surface collectively covering the connecting ends of the two or more elements, on the basis of the thicknesses and the positions of both ends of the two or more elements connected at the connection point.

Abstract: A storage section stores positional information and a physical amount for each of a plurality of physical amount set points arranged in a three-dimensional model. A division section generates division data corresponding to each of a plurality of second regions obtained by dividing a first region including the three-dimensional model so as to make the number of physical amount set points included in each second region equal. When a position in the three-dimensional model is designated, a search section acquires from the storage section a physical amount for a physical amount set point corresponding to the designated position of physical amount set points which division data corresponding to a second region, of the plurality of second regions, including the designated position includes.

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: In a vascular data generation apparatus, a processor generates first vascular data based on anatomical statistics data about vessels of an organ. This first vascular data has a tree structure representing a vascular network in the organ. The processor further generates second vascular data representing a plurality of vessels that connect a plurality of nodes in a geometric model of the organ with the vascular network represented by the first vascular data.

Abstract: The disclosed method includes: carrying out scale conversion for a first pixel value of each of a plurality of pixels included in an image to generate a second pixel value of the plurality of pixels; applying a reaction-diffusion equation including a diffusion element and a reaction element that is set according to at least the number of types of regions to be extracted, to the second pixel value of each of plural pixels within a certain region of the image a predetermined number of times to generate a third pixel value of each of the plurality of pixels included in the image; and carrying out scale inverse-conversion that is inverse-conversion of the scale conversion, for the third pixel value of each of the plurality of pixels included in the image to generate a fourth pixel value of the plurality of pixels.

Abstract: A disclosed method includes: performing a processing for adjusting positions of voxel data for an object and data of a geometric model for the object; calculating, for each voxel included in a range defined by a cross section among plural voxels that are included in the voxel data, a voxel value of the voxel from physical values in elements of the geometric model, which are included in a predetermined range of the voxel, based on a relation between the cross section and vectors; and rendering an image by using the voxel value calculated for each voxel. A vector of the vectors is set for one element of plural elements included in the geometric model, the vectors represent a direction of an inner structure of the object, and the cross section is set for the voxel data and the geometric model data.

Abstract: A biological simulation method includes calculating a behavior of a material contained in a cell of an organ of a biological body, calculating a behavior of the cell based on the calculated behavior of the material, calculating a behavior of the organ based on the calculated behavior of the cell, reflecting the calculated behavior of the organ to the behavior of the cell, and reflecting the behavior of the cell to which the behavior of the organ has been reflected to the behavior of the material.

Abstract: A biological simulation method of causing a computer to execute following steps. Firstly, the computer calculates states of a plurality of actins and states of a plurality of myosins in a sarcomere contained in a muscle of a biological body using a model that defines a plurality of states of the actins and a plurality of states of the myosins and transition rates between the states. Secondly, the computer calculates behaviors of the respective actins and behaviors of the respective myosins based on the states of the actins and the states of the myosins, respectively. Thirdly, the computer calculates a behavior of the sarcomere based on the behaviors of the actins and the behaviors of the myosins. Fourthly, the computer calculates a behavior of the muscle based on the behavior of the sarcomere.

Abstract: This method includes: generating data of a mask surface with respect to visualization data arranged in a virtual three-dimensional space, for calculation values at respective calculation points; identifying, from a first data storage storing, as time-series data, positions of the calculation points and calculation values at the calculation points, a first point whose position is closest to a predetermined point on the mask surface; reading out, from the first data storage, a position of the identified first point in each time; arranging the mask surface in each time based on a direction of a user's sight line and the read position in each time so as to make the mask surface perpendicular to the direction of the user's sight line and have the predetermined point on the mask surface arranged at the read position; and drawing polygon data of the visualization data and the mask surface in time series.