Abstract:
This invention relates to rearranging a cluster map of voxels in an image aiming at the reduction of sub-cluster scatter. The cluster map that includes two or more cluster levels is displayed to the user along with the distribution of the voxels within each respective cluster levels. The aim is to enable the user to evaluate the quality of the cluster map and based on the evaluation to change the distribution of the voxels. Such a change in the distribution will result in an update of the cluster map.
Abstract:
This invention relates to a method of combining multiple binary cluster maps into a single cluster map; where each respective binary cluster map represents characteristic information and the single cluster map represent the sum of the characteristic information. Initially, each respective binary cluster map is assigned with a reliability factor for indicating the reliability of the binary cluster map. These factor values are then used to determine a reliability vector comprising reliability factor elements, where each respective reliability factor element is associated to certain cluster map area in the single cluster map and indicates the reliability of cluster map are. In that way, the single cluster map can be viewed with respect to the reliability.
Abstract:
This invention relates to rearranging a cluster map of voxels in an image aiming at the reduction of sub-cluster scatter. The cluster map that includes two or more cluster levels is displayed to the user along with the distribution of the voxels within each respective cluster levels. The aim is to enable the user to evaluate the quality of the cluster map and based on the evaluation to change the distribution of the voxels. Such a change in the distribution will result in an update of the cluster map.
Abstract:
This relates to a method of automatically selecting preferred voxels from a group of voxels for pharmacokinetic modeling of a biological system, where the voxels contain data points indicating a change of activity-levels over time. For each respective voxel the changes of the data points over time with at least one noise level value, where the comparing is performed in accordance to a pre-defined selection rule. Then, those voxels where the result of the comparing obeys the selection rule are then selected as preferred voxels.