Paper
24 March 2014 Classification based micro-calcification detection using discriminative restricted Boltzmann machine in digitized mammograms
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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.
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SeungYeon Shin, Soochan Lee, and Il Dong Yun "Classification based micro-calcification detection using discriminative restricted Boltzmann machine in digitized mammograms", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90351L (24 March 2014); https://doi.org/10.1117/12.2043316
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Mammography

Tissues

Image enhancement

Breast cancer

Data modeling

Computer aided diagnosis and therapy

Image compression

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