Conference Paper (international conference)
,
: Proceedings of the Tenth International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2014, p. 65-72 , Eds: Yetongno Kokou, Dipanda Albert, Chbeir Richard
: Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2014), (Marrakech, MA, 23.11.2014-27.11.2014)
: GA14-10911S, GA ČR
: mammography, image enhancement, MRF, textural models
: http://library.utia.cas.cz/separaty/2014/RO/haindl-0436549.pdf
(eng): Five 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 are available.
: BD