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

Michael P. Chwialkowski; Sourabh Basak; Dennis P. Pfeifer; Robert W. Parkey; Ronald M. Peshock M.D.

doi:10.1117/12.23559

1 November 1990 Anatomy-sensitive optimization of edge-detection algorithms for MR images of the lower spine

Michael P. Chwialkowski, Sourabh Basak, Dennis P. Pfeifer, Robert W. Parkey, Ronald M. Peshock M.D.

Proceedings Volume 1349, Applications of Digital Image Processing XIII; (1990) https://doi.org/10.1117/12.23559
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

Abstract

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 humananatomy only a few successful attempts have been reported in the past2''3''4''5. In this paper a new concept is presented which uses the incremental estimation of an edge by multi-pass application of a nonlinear 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.

Citation Download Citation

Michael P. Chwialkowski, Sourabh Basak, Dennis P. Pfeifer, Robert W. Parkey, and Ronald M. Peshock M.D. "Anatomy-sensitive optimization of edge-detection algorithms for MR images of the lower spine", Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); https://doi.org/10.1117/12.23559

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