Many biomedical applications require accurate non-rigid image registration that can cope with complex deformations. However, popular diffeomorphic Demons algorithms suffer from difficulties for and serious distortions since they only use greyscale gradient information. To address these difficulties, a new algorithm is proposed using hierarchical neighbourhood spectral features namely HNSF Log-D...

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We introduce and realize demons that follow a customary gambling strategy to stop nonequilibrium process at stochastic times. derive second-law-like inequalities for the average work done in presence of gambling, universal stopping-time fluctuation relations classical quantum non-stationary processes. test experimentally our results single-electron box, where an electrostatic potential drives d...

Image registration is a building block for many applications in computer vision and medical imaging. However the current methods are limited when large and highly non-local deformations are present. In this paper, we introduce a new direct feature matching technique for non-parametric image registration where efficient nearest-neighbor searches find global correspondences between intensity, spa...

PURPOSE The accuracy and convergence behavior of a variant of the Demons deformable registration algorithm were investigated for use in cone-beam CT (CBCT)-guided procedures of the head and neck. Online use of deformable registration for guidance of therapeutic procedures such as image-guided surgery or radiation therapy places trade-offs on accuracy and computational expense. This work describ...