Publication details

Monography Chapter

Digital Mammogram Enhancement

Haindl Michal, Remeš Václav

: Mammography Techniques and Review, p. 63-78 , Eds: Fernandes Fabiano Cavalcanti, Brasil Lourdes Mattos, da Veiga Guadagnin Renato

: GA14-10911S, GA ČR

: mammogram enhancement, Markov random field, texture model

: 10.5772/60988


(eng): 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.

: BD