Learning-based Neuroimage Registration

Leonid Teverovskiy and Yanxi Liu
tech. report CMU-RI-TR-04-59, Robotics Institute, Carnegie Mellon University, October, 2004


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Abstract
Neuroimage registration has been a crucial area of research in medical image analysis for many years. Aligning brain images of different subjects in such a way that same anatomical structures correspond spatially is required in many different applications, including neuroimage classification, computer aided diagnosis, statistical quanti?ation of human brains and neuroimage segmentation. We combine statistical learning, computer vision and medical image analysis to propose a multiresolution framework for learning-based neuroimage registration. Our approach has four distinct characteristics not present in other registration methods. First, instead of subjectively choosing which features to use for registration, we employ feature selection at di?rent image scales to learn an appropriate subset of features for registering a specific pair of neuroimages. Second, we use interesting-voxel selection to identify image voxels that have the most distinct image feature vectors. These voxels are then used to estimate the deformation field for registration. Third, we iteratively improve our choice of features and interesting voxels during registration process. Fourth, we create and take advantage of a statistical model containing information on image feature distributions in each anatomical location.

Keywords
feature vectors, feature selection, interesting voxels, deformable registration, image pyramid, thin plate splines, RANSAC

Notes
Sponsor: NIH
Grant ID: AG05133, DA015900-01
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center
Associated Lab(s) / Group(s): Medical Robotics and Computer Assisted Surgery, Computational Symmetry, Biomedical Image Analysis
Associated Project(s): A Statistical Quantification of Human Brain Asymmetry
Number of pages: 9

Text Reference
Leonid Teverovskiy and Yanxi Liu, "Learning-based Neuroimage Registration," tech. report CMU-RI-TR-04-59, Robotics Institute, Carnegie Mellon University, October, 2004

BibTeX Reference
@techreport{Teverovskiy_2004_4869,
   author = "Leonid Teverovskiy and Yanxi Liu",
   title = "Learning-based Neuroimage Registration",
   booktitle = "",
   institution = "Robotics Institute",
   month = "October",
   year = "2004",
   number= "CMU-RI-TR-04-59",
   address= "Pittsburgh, PA",
}