Nonrigid image registration is a crucial task to study local structural/volumetric change in many applications. The presence and resection of brain tumor in pre- and intra-operative brain images will greatly distort local anatomical structure and introduce non-corresponding outlier features. This can cause serious conflicts in achieving a smoothly varying deformation field in nonrigid registration. In this paper, a novel regularizing scheme, which is based on local anisotropic structure and Joint Saliency Map weighted regularization, is introduced in registration to aim at handling local complex deformation and outliers. The sparse displacement is regularized to adapt its smoothness as well as orientation according to the local anisotropic structure. Moreover, the Joint Saliency Map guides the assignment of data certainty so that the reliable corresponding structural voxels are emphasized in regularization. The results show that our method is sufficiently accurate and effective to both local large deformation and outliers while maintaining an overall smooth deformation field.

Date Published: 8 July 2011
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 800913 (8 July 2011); doi: 10.1117/12.896137

Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)