Abstract:
A processor extracts, from an image including a plurality of structures that spatially continuously present and whose corresponding labels have a hierarchy, respective key points of the plurality of structures in association with labels of a first layer; uses the key points as nodes to derive a graph structure in which the labels of the first layer are associated with the nodes; and associates the nodes with labels of a second layer lower than the first layer by analyzing the graph structure.
Abstract:
The medical image processing apparatus includes a medical image acquisition unit that acquires a medical image; and a lesion detection unit that detects a lesion region in the medical image. The lesion detection unit includes a first identifier that identifies a lesion region candidate in the medical image and a second identifier that identifies whether the lesion region candidate identified by the first identifier is a blood vessel region, and detects the lesion region candidate that is not identified as the blood vessel region by the second identifier as the lesion region.
Abstract:
A division position search unit searches for a division position on an edge present on a path from a second end point, which is one of plural end points of a tree structure of a three-dimensional object other than a first end point, toward the first end point, and at the division position, the size of a downstream tree structure spreading from the division position toward a direction opposite to the first end point changing from a size within an output range of a three-dimensional object creation apparatus to a size exceeding the output range. Then, a division unit divides, at the division position, the three-dimensional object into a division object the size of which is within the output range and a remaining object. An output unit outputs the division object to the three-dimensional object creation apparatus.
Abstract:
A path detection-use graph structure is generated based on a plurality of nodes representing the plurality of linear structures, and a path that is included in the generated path detection-use graph structure and connects a plurality of root nodes representing points of origin of the plurality of linear structures to each other is detected. Then, based on a predetermined condition representing a feature of an erroneous connection edge erroneously connecting two nodes that are to belong to different graph structures to each other, a connection cost is set for each of edges forming the path so that the erroneous connection edge is hard to connect, and based on the set connection costs, the plurality of graph structures corresponding respectively to the plurality of linear structures are generated.
Abstract:
A graph estimated to represent hepatic veins is extracted from image data. Shape models representing partial tree structures branched from a point of origin within a tree structure representing a common shape of hepatic veins are obtained. A cost function correlates the graph with the shape models. Whether parts extending from the peaks of correlated graph parts and not correlated with a shape model exist within the extracted graph is judged. Positional data of the peaks are obtained as data representing the position of the point of origin in the case that no such parts exist, or positional data of a node closest to an estimated position of the point of origin, specified by tracing along the nodes of such parts from the peaks to approach the estimated position, is obtained as data representing the position of the point of origin, in the case that such parts exist.