Multiple sclerosis lesion segmentation using dictionary learning and sparse coding

Weiss N, Rueckert D, Rao A (2013)

Publication Type: Conference contribution

Publication year: 2013

Journal

Lecture Notes in Computer Science Springer Verlag

Book Volume: 8149 LNCS

Pages Range: 735-742

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: JPN

ISBN: 9783642408106

DOI: 10.1007/978-3-642-40811-3_92

Abstract

The segmentation of lesions in the brain during the development of Multiple Sclerosis is part of the diagnostic assessment for this disease and gives information on its current severity. This laborious process is still carried out in a manual or semiautomatic fashion by clinicians because published automatic approaches have not been universal enough to be widely employed in clinical practice. Thus Multiple Sclerosis lesion segmentation remains an open problem. In this paper we present a new unsupervised approach addressing this problem with dictionary learning and sparse coding methods. We show its general applicability to the problem of lesion segmentation by evaluating our approach on synthetic and clinical image data and comparing it to state-of-the-art methods. Furthermore the potential of using dictionary learning and sparse coding for such segmentation tasks is investigated and various possibilities for further experiments are discussed. © 2013 Springer-Verlag.

Involved external institutions

Universität zu Lübeck DE Germany (DE) Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB)

How to cite

APA:

Weiss, N., Rueckert, D., & Rao, A. (2013). Multiple sclerosis lesion segmentation using dictionary learning and sparse coding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 735-742). JPN.

MLA:

Weiss, Nick, Daniel Rueckert, and Anil Rao. "Multiple sclerosis lesion segmentation using dictionary learning and sparse coding." Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, JPN 2013. 735-742.

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