SURF and Spatial Association Correspondence applied in extraction and matching of feature points from MR images of deformed tissues

The extraction and matching of feature points is very important for measuring deformation fields of MR images. Current methods cannot extract and match enough feature points correctly when non-rigid soft biological tissues are deformed in MR images. The authors have therefore used SURF to extract feature points from initial MR images, utilizing every point in deformed MR images as feature points. Subsequently, SURF descriptors and Spatial Association Correspondence (SAC) of neighboring pixels are utilized to match the corresponding feature points of the initial and deformed MR images. Finally, by clustering the differences between deformed points matched by SURF-SAC with the corresponding points calculated by affine transformation, most incorrect match points can be eliminated. Our experimental results show that the proposed method can extract and match more correct corresponding feature point pairs than SURF and SIFT methods.