Paul Thompson's Research Publications

Spatially And Temporally Adaptive Elastic Template Matching

Submitted to IEEE Transactions on Medical Imaging, Sept. 2000.

Alain Pitiot, Arthur W. Toga, and Paul Thompson

Laboratory of Neuro Imaging, Dept. Neurology, Division of Brain Mapping,
UCLA School of Medicine, Los Angeles CA 90095, USA


Summary. We propose a general elastic matching method to evolve deformable templates over 2D images, for automated structure identification. A prototype template, in the form of a B-spline, is warped in a potential field which guides the deformable contour. In contrast to prior approaches, the potential field is adapted both spatially and temporally. This improves the speed and accuracy of the object extraction process. The potential field is initially designed based on spatial characteristics of edge features in the input image. This guarantees efficient dynamics as early as the first iterations. The potential function, which guides the deformable contour, is also logarithmically re-mapped to improve the global consistency and convergence speed of the evolution process (see below).

Automated Extraction of the Corpus Callosum Boundary in Brain MRI.

We present several adaptive techniques to dynamically refine the potential field along with the deformation process itself, to achieve a better match. We also investigate in detail the pre-processing phase from edge extraction to the construction of the initial edge potential. We integrated the deformation algorithm with techniques to improve the match by modifying the internal structure of the template as well as evolving its geometry. We focused on understanding the features of template matching that are most beneficial in terms of the achieved match. Finally, experiments using real medical and photographic datasets are presented, with considerations about the efficiency of our method.

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    73-360 Brain Research Institute
    UCLA Medical Center
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