Titlebook: Machine Learning in Medical Imaging; Third International Fei Wang,Dinggang Shen,Kenji Suzuki Conference proceedings 2012 Springer-Verlag B

決定性

Dense Deformation Reconstruction via Sparse Coding,ation method and obtain correspondences on a fixed set of landmarks in the template, as well as the respective dense deformation field. Then, we can build two dictionaries to, respectively, save the landmark correspondences and their dense deformations from all training images at the same indexing o

畫布

Gastric

Sparse Patch-Guided Deformation Estimation for Improved Image Registration,o the template in the training stage, the following three steps can be used to register any given subject image. ., for each key point in the subject, we can construct a coupled dictionary from the nearby patches in the training images and their associated deformations, and can then use this diction

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