Mammography Techniques and Review

0445250 - ÚTIA 2016 RIV HR eng M - Monography Chapter
Haindl, Michal - Remeš, Václav
Digital Mammogram Enhancement.
Mammography Techniques and Review. Zagreb: InTech Education and Publishing, 2015 - (Fernandes, F.; Brasil, L.; da Veiga Guadagnin, R.), s. 63-78. ISBN 978-953-51-2138-1
R&D Projects: GA ČR(CZ) GA14-10911S
Institutional support: RVO:67985556
Keywords : mammogram enhancement * Markov random field * texture model
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2015/RO/haindl-0445250.pdf

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.
Permanent Link: http://hdl.handle.net/11104/0247980