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Mammography Techniques and Review
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SYSNO ASEP 0445250 Document Type M - Monograph Chapter R&D Document Type Monograph Chapter Title Digital Mammogram Enhancement Author(s) Haindl, Michal (UTIA-B) RID, ORCID
Remeš, Václav (UTIA-B) RIDNumber of authors 2 Source Title Mammography Techniques and Review. - Zagreb : InTech Education and Publishing, 2015 / Fernandes Fabiano Cavalcanti ; Brasil Lourdes Mattos ; da Veiga Guadagnin Renato - ISBN 978-953-51-2138-1 Pages s. 63-78 Number of pages 16 s. Number of pages 120 Publication form Print - P Language eng - English Country HR - Croatia Keywords mammogram enhancement ; Markov random field ; texture model Subject RIV BD - Theory of Information R&D Projects GA14-10911S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 DOI 10.5772/60988 Annotation Three fully automatic methods for X-ray digital mammogram enhancement based on a fast analytical textural model are presented. These efficient single and double view enhancement methods are based on the underlying two-dimensional adaptive causal autoregressive texture model. The~methods locally predict breast tissue texture from single or double view mammograms and enhance breast tissue abnormalities, such as the sign of a developing cancer, using the estimated model prediction statistics. The~double-view mammogram enhancement is based on the cross-prediction of two mutually registered left and right breasts' mammograms or alternatively a temporal sequence of mammograms. The single-view mammogram enhancement is based on modeling prediction error in case of not the both breasts' mammograms being available. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2016
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