Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15948-0_3
Title: Content-based medical image retrieval with metric learning via rank correlation
Authors: Huang, W.
Chan, K.L.
Li, H.
Lim, J.H.
Liu, J.
Wong, T.Y. 
Issue Date: 2010
Source: Huang, W.,Chan, K.L.,Li, H.,Lim, J.H.,Liu, J.,Wong, T.Y. (2010). Content-based medical image retrieval with metric learning via rank correlation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6357 LNCS : 18-25. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-15948-0_3
Abstract: A novel content-based medical image retrieval method with metric learning via rank correlation is proposed in this paper. A new rank correlation measure is proposed to learn a metric encoding the pairwise similarity between images via direct optimization. Our method has been evaluated with a large population-based dataset composed of 5000 slit-lamp images with different nuclear cataract severities. Experimental results and statistical analysis demonstrate the superiority of our method over several popular metric learning methods in content-based slit-lamp image retrieval. © 2010 Springer-Verlag Berlin Heidelberg.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/109749
ISBN: 3642159478
ISSN: 03029743
DOI: 10.1007/978-3-642-15948-0_3
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