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Texture descriptors applied to digital mammography
- Publication Year :
- 2008
-
Abstract
- Breast cancer is the second cause of death among women cancers. Computer Aided Detection has been demon- strated an useful tool for early diagnosis, a crucial as- pect for a high survival rate. In this context, several re- search works have incorporated texture features in mam- mographic image segmentation and description such as Gray-Level co-occurrence matrices, Local Binary Pat- terns, and many others. This paper presents an approach for breast density classi¯cation based on segmentation and texture feature extraction techniques in order to clas- sify digital mammograms according to their internal tis- sue. The aim of this work is to compare di®erent texture descriptors on the same framework (same algorithms for segmentation and classi¯cation, as well as same images). Extensive results prove the feasibility of the proposed ap- proach.<br />Postprint (published version)
Details
- Database :
- OAIster
- Notes :
- 6 p., application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.ocn978330781
- Document Type :
- Electronic Resource