Publication details

Adaptive Model-Based Mammogram Enhancement

Conference Paper (international conference)

Haindl Michal, Remeš Václav


serial: 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

action: Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2014), (Marrakech, MA, 23.11.2014-27.11.2014)

project(s): GA14-10911S, GA ČR

keywords: mammography, image enhancement, MRF, textural models

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abstract (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.

RIV: BD