Proceedings Paper
Classification based micro-calcification detection using discriminative restricted Boltzmann machine in digitized mammograms| Format | Member Price | Non-Member Price |
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Paper Abstract
We present a new method for automatic detection of micro-calcifications using the Discriminative Restricted Boltzmann Machine (DRBM). The DRBM is used to automatically learn the specific features which distinguish micro-calcifications from normal tissue as well as their morphological variations. Within the DRBM, low level image structures that are specific features of micro-calcifications are automatically captured without any appropriate feature selection based on expert knowledge or time-consuming hand-tuning, which was required for previous methods. Experimental evaluation conducted on a set of 33 mammograms gave a result of area under Receiver Operating Characteristics (ROC) curve 0.8294, which showed the effectiveness of the proposed method.
Paper Details
Date Published: 24 March 2014
PDF: 6 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90351L (24 March 2014); doi: 10.1117/12.2043316
Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)
PDF: 6 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90351L (24 March 2014); doi: 10.1117/12.2043316
Show Author Affiliations
SeungYeon Shin, Seoul National Univ. (Korea, Republic of)
Soochan Lee, Samsung Electronics Co., Ltd. (Korea, Republic of)
Soochan Lee, Samsung Electronics Co., Ltd. (Korea, Republic of)
Il Dong Yun, Hankuk Univ. of Foreign Studies (Korea, Republic of)
Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)
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