Abstract:
A three-dimensional medical image obtainment unit that obtains a three-dimensional medical image of a chest, a bronchial structure extraction unit that extracts a bronchial structure from the three-dimensional medical image, a divided lung region obtainment unit that divides, based on the divergence of the bronchial structure, the bronchial structure into plural bronchial structures, and obtains plural divided lung regions based on the plural divided bronchial structures, a distance image generation unit that generates, based on the plural divided lung regions, a distance image based on a distance between each voxel in an entire region excluding at least one of the plural divided lung regions and each of the plural divided lung regions, and a border non-existing region extraction unit that extracts, based on the distance image generated by the distance image generation unit, a border non-existing region, which does not include any borders of the divided lung regions, are provided.
Abstract:
An information processing device detects a cell candidate region for determining a unity of a cell from a vessel image obtained by imaging a vessel in which the cell is seeded and includes at least one processor. The processor performs an acquisition process of acquiring the vessel image, performs a detection process of detecting a cell region including the cell and a cell-like region including an object similar to the cell as the cell candidate regions from the acquired vessel image, and an output process of outputting information indicating the detected cell candidate regions.
Abstract:
In a CPR image generation apparatus, method, and program, a CPR image is generated so as to include a region of interest, such as a branch, a myocardium, a plaque, and a lesion. A structure extraction unit 22 extracts a coronary artery region 30 from a three-dimensional image G0. A cross section setting unit 23 sets a cross section Pk perpendicular to a reference line L0 for each point on the reference line L0 in the coronary artery region 30. In a case where a region of interest is present on each cross section Pk, a cutting plane determination unit 24 determines one cutting plane Ck in each cross section including the reference line L0 and the region of interest. An image generation unit 25 generates a CPR image G10 including the cutting plane Ck.
Abstract:
Provided is an information processing device that performs display control to display a vessel image obtained by imaging a vessel in which a cell is seeded on a display and includes at least one processor. The processor acquires two or more vessel images obtained by imaging the same vessel at different dates and times and displays the acquired two or more vessel images on the display such that different imaging dates and times are distinguishable.
Abstract:
An initial position aligning unit performs initial positional alignment of a video and simulation data, and a position aligning unit performs positional alignment of the video and the simulation data. A first movement detecting unit detects movements of reference points which are set within a first image of the video, and a second movement detecting unit detects movement of a camera. A degree of reliability calculating unit compares the first and second movements to calculate a degree of reliability with respect to the movements of each of the reference points.
Abstract:
For assigning a binary label representing belonging to a target region or not to each pixel in an image: a predicted shape of the target region is set; a pixel group including N pixels is selected, where N is a natural number of 4 or more, which have a positional relationship representing the predicted shape; and an energy function is set, which includes an N-th order term in which a variable is a label of each pixel of the pixel group, so that a value of the N-th order term is at a minimum value when a combination of the labels assigned to the pixels of the pixel group is a pattern matching the predicted shape, and increases in stages along with an increase in a number of pixels to which a label different from the pattern is assigned. The labeling is performed by minimizing the energy function.
Abstract:
When a virtual-endoscopic-image is generated from a three-dimensional-image representing a tubular-organ, a predetermined range is set in the vicinity of a viewpoint set in advance in the three-dimensional-image, and each of a lumen-region and a wall-region of the tubular-organ in the set range is identified. A voxel-value or a voxel-value-interval constituting a boundary between a range of voxel values in the identified lumen-region and a range of voxel values in the identified wall-region is obtained based on information about voxel-values in the identified lumen-region and information about voxel-values in the identified wall-region, and an opacity-curve representing a relationship between voxel values and opacity is set in such a manner that the opacity changes from a value representing a transparent-state to a value representing an opaque-state at the voxel-value or in the voxel-value-interval. The virtual-endoscopic-image is generated from the three-dimensional-image by volume rendering using the set viewpoint and the set opacity-curve.