Imaging method for sampling a cross-section plane in a three-dimensional (3d) image data volume

PH008590 20 ABSTRACT: Automated Vessel Analysis (AVA) allows qualitative and quantitative feedback to the user, regarding vessel pathologies (such as stenosis), with a minimum of user input. However, present algorithms may be unsuitable for large datasets, especially because of the rather long pre-processing time. Here an imaging method for placing probes on the vessel tree is presented that does not require any pre-processing time at 5 all, and performs very well on (very) large datasets, both in terms of speed and memory consumption. The method comprises the steps: classifying voxels of a 3D data volume as voxels of the first, the second or further types, determining a starting voxel in a tubular structure of voxels of the first type, determining the centre line in the proximity ofthe starting voxel, and fitting a plane through the starting voxel, perpendicular to the 10 centre line. Further the contour of the vessel cross-section on the plane can be determined, as well as its maximum, minimum and average diameter, and the area of the vessel cross-section.