Abstract: A computer-implemented method, performed by a computing device, comprises: receiving raw multispectral medical imaging data, which was acquired via an energy-resolved medical imaging technique; determining a scope of analysis of the raw multispectral medical imaging data; selecting at least one spectral map based on the scope of analysis; and processing the raw multispectral medical imaging data to generate at least one medical image based on the at least one spectral map.

Abstract: A computer-implemented method of generating a further glyph representation for use in a rendering process, comprises: determining a first plurality of locations in the further glyph representation corresponding with a respective plurality of source locations in a source glyph representation; setting respective first indices for the first plurality of locations based on values associated with the respective plurality of source locations; setting, for each location of a further plurality of locations in the further glyph representation, respective second indices based on a relationship between the location and one or more source locations, wherein the further plurality of locations include the first plurality of locations and a second plurality of locations; and storing the respective first and second indices in association with respective locations. A computer-implemented method of rendering a glyph using the further glyph representation is also described.

Abstract: One or more example embodiments relates to a processing of medical images when a medical image is provided together with at least one annotational data element. A region of interest is identified, which is currently relevant for a user. After identifying such a region of interest, which may be done dynamically or continuously, the at least one annotational data element is provided with an appearance so that the region of interest is obscured as less as possible.

Abstract: In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.

Abstract: In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.

Abstract: In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.

Abstract: In order to decrease a memory footprint for volume rendering, distance field information is adaptively compressed and merged with an existing data structure having unused memory to form a merged dataset. During rendering, the merged dataset is sampled, and a sampled value is used to identify a look-up table for a corresponding voxel or is decompressed and used to skip empty space.