A General Fast Registration Framework by Learning Deformation-Appearance Correlation

• Published in: IEEE transactions on image processing Vol. 21; no. 4; pp. 1823 - 1833
• Main Authors: Kim, Minjeong, Wu, Guorong, Yap, Pew-Thian, Shen, Dinggang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2012
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Brain modeling; Correlation; Deformable models; Deformation prediction; fast image registration; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Pattern Recognition, Automated - methods; Principal component analysis; principal component analysis (PCA); Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique; support vector regression (SVR); Training

In this paper, we propose a general framework for performance improvement of the current state-of-the-art registration algorithms in terms of both accuracy and computation time. The key concept involves rapid prediction of a deformation field for registration initialization, which is achieved by a s...