Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry configured: to generate a projection image by implementing an intensity projection on a plurality of two-dimensional images structuring three-dimensional volume data rendering a tubular organ; to obtain a mapping matrix of the intensity projection; to annotate the tubular organ in the projection image; and to identify the tubular organ in the three-dimensional volume data, by inversely mapping the tubular organ annotated in the projection image onto the three-dimensional volume data while using the mapping matrix.

Abstract: An image segmentation apparatus according to an embodiment of the present disclosure includes processing circuitry. The processing circuitry is configured to obtain a massive region to which labeling information is attached and a tubular region to which labeling information is attached. By using the labeling information of the massive region and the labeling information of the tubular region, the processing circuitry is configured to generate a region to be segmented and a non-boundary region, by carrying out a distance transformation. The processing circuitry is configured to generate a classifier for classifying spatial coordinates, by using the labeling information of the non-boundary region and labeling information in a specific position determined on the basis of the region to be segmented and the tubular region. The processing circuitry is configured to segment voxels in the region to be segmented by using the classifier and to thus determine a final segmentation result.

Abstract: A segmentation model learning method according to an embodiment includes learning that, based on a loss function value, includes performing supervised learning of the voxels in medical image data according to the region to which the voxels belong.

Abstract: A medical image processing apparatus according to one embodiment includes processing circuitry. The processing circuitry trains an attention model by using a medical image and a mask image that is obtained by performing mask processing on a region other than a region of interest in the medical image, trains an image processing model by using the medical image, a heatmap corresponding to the medical image, and an attention feature that indicates attention of the region of interest in the trained attention model, combines, as an attention image processing model, an attention extraction module that includes an attention module for outputting the attention feature and the trained image processing model, performs processing on the medical image by using the attention image processing model, and generates a heatmap for determining a position of a landmark in the medical image.

Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry configured: to generate a projection image by implementing an intensity projection on a plurality of two-dimensional images structuring three-dimensional volume data rendering a tubular organ; to obtain a mapping matrix of the intensity projection; to annotate the tubular organ in the projection image; and to identify the tubular organ in the three-dimensional volume data, by inversely mapping the tubular organ annotated in the projection image onto the three-dimensional volume data while using the mapping matrix.