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6 June 2000 Validation of probabilistic anatomical shape atlases
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Registration of anatomical images is useful for many applications including image segmentation, characterization of normal and abnormal shape, and creating deformable anatomical shape atlases. The usefulness of the information derived from image registration depends on the degree of anatomically meaningful correspondence between the images. We assume that an ideal image registration algorithm can determine an unique correspondence mapping between any two image volumes imaged from a homogeneous population of anatomies; and that these transformations have the properties of invertibility and transitivity. Unfortunately, current image registration algorithms are far from ideal. In this paper we test the invertibility and transitivity of transformations computed from a 'traditional' and a consistent linear-elastic registration algorithm. Invertibility of the transformations was evaluated by comparing the composition of transformations from image A-to-B and B-to-A to the identity mapping. Transitivity of the transformations was evaluated by measuring the difference between the identity mapping and the composition the transformations from image A-to-B, B-to-C, and C-to-A. Transformations were generated by matching computer generated phantoms, CT data of infant heads, and MRI data of adult brains. The consistent algorithm out performed the 'traditional' algorithm by 8 to 16 times for the invertibility test and 2 to 5 times for the transitivity test.
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Hans J. Johnson, Gary E. Christensen, Jeffrey L. Marsh M.D., and Michael W. Vannier M.D. "Validation of probabilistic anatomical shape atlases", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000);

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