title: An implicit sliding-motion preserving regularisation via bilateral filtering for deformable image registration.
abstract: Several biomedical applications require accurate image registration that can cope effectively with complex organ deformations. This paper addresses this problem by introducing a generic deformable registration algorithm with a new regularization scheme, which is performed through bilateral filtering of the deformation field. The proposed approach is primarily designed to handle smooth deformations both between and within body structures, and also more challenging deformation discontinuities exhibited by sliding organs. The conventional Gaussian smoothing of deformation fields is replaced by a bilateral filtering procedure, which compromises between the spatial smoothness and local intensity similarity kernels, and is further supported by a deformation field similarity kernel. Moreover, the presented framework does not require any explicit prior knowledge about the organ motion properties (e.g. segmentation) and therefore forms a fully automated registration technique. Validation was performed using synthetic phantom data and publicly available clinical 4D CT lung data sets. In both cases, the quantitative analysis shows improved accuracy when compared to conventional Gaussian smoothing. In addition, we provide experimental evidence that masking the lungs in order to avoid the problem of sliding motion during registration performs similarly in terms of the target registration error when compared to the proposed approach, however it requires accurate lung segmentation. Finally, quantification of the level and location of detected sliding motion yields visually plausible results by demonstrating noticeable sliding at the pleural cavity boundaries.
authors: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK. Electronic address: bartlomiej.papiez@eng.ox.ac.uk.
authors: Bartłomiej W
authors: BW
authors: Papież
authors: Institute of Medical Informatics, University of Lübeck, Germany.
authors: Mattias P
authors: MP
authors: Heinrich
authors: Institut de Mathématiques de Toulouse (UMR 5219), Université Paul Sabatier, France.
authors: Jérome
authors: J
authors: Fehrenbach
authors: Institut de Mathématiques de Toulouse (UMR 5219), CNRS, France.
authors: Laurent
authors: L
authors: Risser
authors: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK.
authors: Julia A
authors: JA
authors: Schnabel
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
keywords: Bilateral filtering; Nonrigid registration; Regularisation; Respiratory motion; Sliding motion