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