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Unsupervised Mammograms Segmentation
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SYSNO ASEP 0317588 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Unsupervised Mammograms Segmentation Title Neřízená segmentace mamogramů Author(s) Haindl, Michal (UTIA-B) RID, ORCID
Mikeš, Stanislav (UTIA-B) RIDSource Title Proceedings of the 19th International Conference on Pattern Recognition. - Los Alamitos : IEEE Press, 2008 - ISBN 978-1-4244-2174-9 Pages s. 676-679 Number of pages 4 s. Publication form www - www Action 19th International Conference on Pattern Recognition Event date 07.12.2008-11.12.2008 VEvent location Tampa Country US - United States Event type WRD Language eng - English Country US - United States Keywords mammography ; cancer detection ; image unsupervised segmentation ; Markov random fields Subject RIV BD - Theory of Information R&D Projects 1ET400750407 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) IAA2075302 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation We present a multiscale unsupervised segmenter for automatic detection of potentially cancerous regions of interest containing fibroglandular tissue in digital screening mammography. The mammogram tissue textures are locally represented by four causal multispectral random field models recursively evaluated for each pixel and several scales. The segmentation part of the algorithm is based on the underlying Gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous mammogram segments is reached. The performance of the presented method is verified on the Digital Database for Screening Mammography (DDSM) from the University of South Florida as well as extensively tested on the Prague Texture Segmentation Benchmark and compares favourably with several alternative unsupervised texture segmentation methods. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2010
Number of the records: 1