Regularity-guaranteed transformation estimation in medical image registration

Bibo Shi; Jundong Liu

doi:10.1117/12.911083

14 February 2012 Regularity-guaranteed transformation estimation in medical image registration

Bibo Shi, Jundong Liu

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83141W (2012) https://doi.org/10.1117/12.911083
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

In addition to seeking geometric correspondence between the inputs, a legitimate image registration algorithm should also keep the estimated transformation meaningful or regular. In this paper, we present a mathematically sound formulation that explicitly controls the deformation to keep each grid in a meaningful shape over the entire geometric matching procedure. The deformation regularity conditions are enforced by maintaining all the moving neighbors as non-twist grids. In contrast to similar works, our model differentiates and formulates the convex and concave update cases under an efficient and straightforward point-line/surface orientation framework, and uses equality constraints to guarantee grid regularity and prevent folding. Experiments on MR images are presented to show the improvements made by our model over the popular Demon's and DCT-based registration algorithms.

Citation Download Citation

Bibo Shi and Jundong Liu "Regularity-guaranteed transformation estimation in medical image registration", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83141W (14 February 2012); https://doi.org/10.1117/12.911083

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