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Proceedings Paper

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation
Author(s): Koen Vijverberg; Mohsen Ghafoorian; Inge W. M. van Uden; Frank-Erik de Leeuw; Bram Platel; Tom Heskes
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Paper Abstract

Cerebral small vessel disease (SVD) is a disorder frequently found among the old people and is associated with deterioration in cognitive performance, parkinsonism, motor and mood impairments. White matter hyperintensities (WMH) as well as lacunes, microbleeds and subcortical brain atrophy are part of the spectrum of image findings, related to SVD. Accurate segmentation of WMHs is important for prognosis and diagnosis of multiple neurological disorders such as MS and SVD. Almost all of the published (semi-)automated WMH detection models employ multiple complex hand-crafted features, which require in-depth domain knowledge. In this paper we propose to apply a single-layer network unsupervised feature learning (USFL) method to avoid hand-crafted features, but rather to automatically learn a more efficient set of features. Experimental results show that a computer aided detection system with a USFL system outperforms a hand-crafted approach. Moreover, since the two feature sets have complementary properties, a hybrid system that makes use of both hand-crafted and unsupervised learned features, shows a significant performance boost compared to each system separately, getting close to the performance of an independent human expert.

Paper Details

Date Published: 24 March 2016
PDF: 7 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97851C (24 March 2016); doi: 10.1117/12.2216409
Show Author Affiliations
Koen Vijverberg, Radboud Univ. Nijmegen (Netherlands)
Radboud Univ. Medical Ctr (Netherlands)
Mohsen Ghafoorian, Radboud Univ. Nijmegen (Netherlands)
Radboud Univ. Medical Ctr. (Netherlands)
Inge W. M. van Uden, Radboud Univ. Medical Ctr. (Netherlands)
Frank-Erik de Leeuw, Radboud Univ. Medical Ctr. (Netherlands)
Bram Platel, Radboud Univ. Medical Ctr. (Netherlands)
Tom Heskes, Radboud Univ. Nijmegen (Netherlands)

Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato, Editor(s)

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