title: Registration using sparse free-form deformations.
abstract: Non-rigid image registration using free-form deformations (FFD) is a widely used technique in medical image registration. The balance between robustness and accuracy is controlled by the control point grid spacing and the amount of regularization. In this paper, we revisit the classic FFD registration approach and propose a sparse representation for FFDs using the principles of compressed sensing. The sparse free-form deformation model (SFFD) can capture fine local details such as motion discontinuities without sacrificing robustness. We demonstrate the capabilities of the proposed framework to accurately estimate smooth as well as discontinuous deformations in 2D and 3D image sequences. Compared to the classic FFD approach, a significant increase in registration accuracy can be observed in natural images (61%) as well as in cardiac MR images (53%) with discontinuous motions.
authors.affiliation: Biomedical Image Analysis Group, Imperial College London, UK.
authors.forename: Wenzhe
authors.initials: W
authors.lastname: Shi
authors.forename: Xiahai
authors.initials: X
authors.lastname: Zhuang
authors.forename: Luis
authors.initials: L
authors.lastname: Pizarro
authors.forename: Wenjia
authors.initials: W
authors.lastname: Bai
authors.forename: Haiyan
authors.initials: H
authors.lastname: Wang
authors.forename: Kai-Pin
authors.initials: KP
authors.lastname: Tung
authors.forename: Philip
authors.initials: P
authors.lastname: Edwards
authors.forename: Daniel
authors.initials: D
authors.lastname: Rueckert
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique