Efficient textural model-based mammogram enhancement

M. Haindl, Václav Remes
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引用次数: 1

Abstract

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.
基于纹理模型的高效乳房x线增强
提出了一种基于底层二维自适应因果自回归纹理模型的x线数字乳房x线多视图增强方法。该方法通过多视图乳房x光片局部预测乳房组织纹理,并利用估计的模型预测误差来增强乳房组织异常,例如正在发展的癌症迹象。乳房x光片增强是基于左、右乳房x光片相互注册的交叉预测误差,或者如果两个乳房的x光片都不可用,则基于单视图模型预测误差。
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CiteScore
3.10
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0.00%
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