Using known motion fields for image separation in transparency
Pattern Recognition Letters
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
International Journal of Computer Vision
Motion Layer Extraction in the Presence of Occlusion Using Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
EURASIP Journal on Advances in Signal Processing
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A variational approach for multi-valued velocity field estimation in transparent sequences
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Diffeomorphic registration using b-splines
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Deformable templates using large deformation kinematics
IEEE Transactions on Image Processing
A robust multiscale B-spline function decomposition for estimating motion transparency
IEEE Transactions on Image Processing
Representing moving images with layers
IEEE Transactions on Image Processing
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Accurate estimation of motion in fluoroscopic imaging sequences is critical for improved frame interpolation/extrapolation, tracking of surgical instruments, and Digital Subtraction Angiography (DSA). The projection of multiple transparent objects undergoing multiple complicated deformations in 3D onto a single 2D view makes this motion estimation problem quite challenging and ill-suited to existing techniques used in medical image analysis. We propose a novel method for jointly decomposing the observed image into a set of additive layers each associated with its corresponding smooth nonlinear deformation, which together model the non-smooth motion observed in the projection images across several frames. A total variation based regularization penalty is used to incorporate the known structure of the input frames for well posedness of the layer separation problem. We present the use of this model for frame interpolation and artifact reduction in DSA. Results are included from synthetic and real clinical datasets.