Efficient textural model-based mammogram enhancement

Efficient textural model-based mammogram enhancement

An efficient method for X-ray digital mammogram multi-view enhancement based on the underlying two-dimensional adaptive causal autoregressive texture model is presented. The method locally predicts breast tissue texture from multi-view mammograms and enhances breast tissue abnormalities, such as the...

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Hauptverfasser: Haindl, Michal, Remes, Vaclav
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Adaptation models
Breast cancer
Computers
Predictive models
Solid modeling
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Remes, Vaclav
description An efficient method for X-ray digital mammogram multi-view enhancement based on the underlying two-dimensional adaptive causal autoregressive texture model is presented. The method locally predicts breast tissue texture from multi-view mammograms and enhances breast tissue abnormalities, such as the sign of a developing cancer, using the estimated model prediction error. The mammo-gram enhancement is based on the cross-prediction error of mutually registered left and right breasts mammograms or on the single-view model prediction error if both breasts' mammograms are not available.
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subjects Adaptation models
Breast cancer
Computers
Predictive models
Solid modeling
title Efficient textural model-based mammogram enhancement
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