TY - GEN
T1 - Learning correspondences in knee MR images from the osteoarthritis initiative
AU - Guerrero, Ricardo
AU - Donoghue, Claire R.
AU - Pizarro, Luis
AU - Rueckert, Daniel
PY - 2012
Y1 - 2012
N2 - Registration is a powerful tool that allows mapping images in a common space in order to aid in their analysis. Accurate registration of images of the knee is challenging to achieve using intensity based registration algorithms. Problems arise due to large anatomical inter-subject differences which causes registrations to fail to converge to an accurate solution. In this work we propose learning correspondences in pairs of images to match self-similarity features, that describe images in terms of their local structure rather than their intensity. We use RANSAC as a robust model estimator. We show a substantial improvement in terms of mean error and standard deviation of 2.13mm and 2.47mm over intensity based registration methods, when comparing landmark alignment error.
AB - Registration is a powerful tool that allows mapping images in a common space in order to aid in their analysis. Accurate registration of images of the knee is challenging to achieve using intensity based registration algorithms. Problems arise due to large anatomical inter-subject differences which causes registrations to fail to converge to an accurate solution. In this work we propose learning correspondences in pairs of images to match self-similarity features, that describe images in terms of their local structure rather than their intensity. We use RANSAC as a robust model estimator. We show a substantial improvement in terms of mean error and standard deviation of 2.13mm and 2.47mm over intensity based registration methods, when comparing landmark alignment error.
UR - http://www.scopus.com/inward/record.url?scp=84870002863&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35428-1_27
DO - 10.1007/978-3-642-35428-1_27
M3 - Conference contribution
AN - SCOPUS:84870002863
SN - 9783642354274
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 218
EP - 225
BT - Machine Learning in Medical Imaging - Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Revised Selected Papers
T2 - 3rd International Workshop on Machine Learning in Medical Imaging, MLMI 2012, Held in conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
Y2 - 1 October 2012 through 1 October 2012
ER -