DocumentCode :
3473802
Title :
Efficient textural model-based mammogram enhancement
Author :
Haindl, Michal ; Remes, Vaclav
Author_Institution :
Fac. of Inf. Technol., CTU in Prague, Prague, Czech Republic
fYear :
2013
fDate :
20-22 June 2013
Firstpage :
522
Lastpage :
523
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.
Keywords :
cancer; image enhancement; image registration; image texture; mammography; medical image processing; 2D adaptive causal autoregressive texture model; X-ray digital mammogram; breast tissue abnormalities; breast tissue texture; cross prediction error; developing breast cancer; estimated model prediction error; mammogram multiview enhancement; multiview mammograms; mutually registered breast mammograms; single view model prediction error; textural model based mammogram enhancement; Adaptation models; Breast cancer; Computers; Predictive models; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on
Conference_Location :
Porto
Type :
conf
DOI :
10.1109/CBMS.2013.6627859
Filename :
6627859
Link To Document :
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