The practice-oriented application of radiation transport programms requires the conditioning of the spatial material distribution of the "simulation world". Depending on the scenario, a description either via geometric objects or via segmentation of the complete world in small partial volumina, so-called voxel, is preferable.
To cover the first case, a binary hierarchic decision management algorithm was developed for AMOS. This algorithm connects every space point with its covering partial volume via unique sequential determination, on which side of a separating surface the point is positioned. Using similar geometrical figures as CAD-programs, technical tasks can be described with this method accurately.
At applications covering living things, i.e. for medical research, fragmentation of space into even so-called voxels is favorable. Such data is directly provided by medical imaging equipment or for standardised phantoms. Both sources can be read by AMOS. For example, the import of DICOM-standard is possible without problems.
The implemented algorithm enables the use of high resolution images, i.e. the CT of a mouse containing 3⋅108 voxels. Every voxel contains its individual data about chemical composition or local density, the latter with a resolution of 0.001 g/ccm.
Over the last years, the steady improvement of imaging systems has been accompanied by a likewise growth of available image data. To make this amount of data applicable on conventional computers, a special method was developed for AMOS. This method reduces the data without downsizing the image resolution. What it does is merge volumes of equal or only slightly differing properties to larger voxels, but leaving the high resolution where the properties differ significantly i.e. at contours of organs.