Anatomy-sensitive optimization of edge detection algorithms for MR images of the lower spine

Due to the relatively large voxel sizes of Magnetic Resonance Images (MRI), the organ boundaries represent an anatomy dependent mixture of multiple tissue types. Subsequently, the image properties at the organ boundaries are highly inconsistent, causing failure to produce closed organ contours using classical edge detectors. While it is widely recognized that solving of the boundary closure problems in MRI is essential for the automated 3-D volumetric reconstruction and quantification of the human anatomy, only a few successful attempts have been reported in the past. In this paper, a new concept is presented which uses the incremental estimation of an edge by multi-pass application of a non-linear, multi-parameter edge detection operator. The operator is optimized using a quality criterion which estimates the continuity of the detected edges either directly, based on a morphological prototype of the organ of interest, or indirectly, based on the percentage of fragmented edges found in an edge-enhanced image. Usefulness of the method is demonstrated on MR studies of the lower spine and human wrist.