Content-based medical image retrieval with metric learning via rank correlation

Wei Huang; Kap Luk Chan; Huiqi Li; Joo Hwee Lim; Jiang Liu; Tien Yin Wong

doi:10.1007/978-3-642-15948-0_3

Content-based medical image retrieval with metric learning via rank correlation

Wei Huang, Kap Luk Chan, Huiqi Li, Joo Hwee Lim, Jiang Liu, Tien Yin Wong

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings
Pages	18-25
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-15948-0_3
Publication status	Published - 2010
Externally published	Yes
Event	1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010 - Beijing, China Duration: 20 Sept 2010 → 20 Sept 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6357 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010
Country/Territory	China
City	Beijing
Period	20/09/10 → 20/09/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-15948-0_3

Cite this

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. In Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings (pp. 18-25). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6357 LNCS). https://doi.org/10.1007/978-3-642-15948-0_3

Huang, Wei ; Chan, Kap Luk ; Li, Huiqi et al. / Content-based medical image retrieval with metric learning via rank correlation. Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings. 2010. pp. 18-25 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8eafb9fe5eac46a69eda607be82280ca,

title = "Content-based medical image retrieval with metric learning via rank correlation",

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.",

author = "Wei Huang and Chan, {Kap Luk} and Huiqi Li and Lim, {Joo Hwee} and Jiang Liu and Wong, {Tien Yin}",

note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; 1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010 ; Conference date: 20-09-2010 Through 20-09-2010",

year = "2010",

doi = "10.1007/978-3-642-15948-0_3",

language = "English",

isbn = "3642159478",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "18--25",

booktitle = "Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings",

}

Huang, W, Chan, KL, Li, H, Lim, JH, Liu, J & Wong, TY 2010, Content-based medical image retrieval with metric learning via rank correlation. in Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6357 LNCS, pp. 18-25, 1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, 20/09/10. https://doi.org/10.1007/978-3-642-15948-0_3

Content-based medical image retrieval with metric learning via rank correlation. / Huang, Wei; Chan, Kap Luk; Li, Huiqi et al.
Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings. 2010. p. 18-25 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6357 LNCS).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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AU - Liu, Jiang

AU - Wong, Tien Yin

PY - 2010

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N2 - 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.

AB - 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.

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DO - 10.1007/978-3-642-15948-0_3

M3 - Conference contribution

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SN - 9783642159473

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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T2 - 1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010

Y2 - 20 September 2010 through 20 September 2010

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Huang W, Chan KL, Li H, Lim JH, Liu J, Wong TY. Content-based medical image retrieval with metric learning via rank correlation. In Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings. 2010. p. 18-25. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-15948-0_3

Content-based medical image retrieval with metric learning via rank correlation

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