SEGMENTATION OF TOMOGRAPHIC DATA WITHOUT IMAGE-RECONSTRUCTION

This paper describes a new technique, called geometric tomography (GT) to process tomographic projections in order to reconstruct the extern al and internal boundaries of objects. One original point is that GT d oes not necessitate the reconstruction of an image of the slice of the object. We show that the segmentation can be performed directly with the raw data, the sinogram produced with the scanner, and that those s egmented shapes can be geometrically transformed into reconstructed sh apes in the usual space. If we are interested in only the boundaries o f the objects, we do not need to reconstruct an image, and therefore o ur method necessitates much less computation than those using traditio nal computed tomography techniques. Experimental results are presented for both synthesized and real data, leading to subpixel positioning o f the reconstructed boundaries. GT gives its best results for sparse, highly contrasted objects such as bones or blood vessels in angiograms , it allows "on the fly" processing of the data, and real time trackin g of the object boundaries.