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Self-Similarity Analysis Applied to 2D Breast Cancer Imaging

Self-Similarity Analysis Applied to 2D Breast Cancer Imaging,10.1109/ICSNC.2007.76,Filipe Soares,Pawel Andruszkiewic,Mário M. Freire,Paulo Cruz,Manuel

Self-Similarity Analysis Applied to 2D Breast Cancer Imaging   (Citations: 3)
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This article presents a new trend in computerized medical image analysis of breast cancer features, exist- ing in mammograms (grey scale 2D images), based on recent approaches of the self-similarity formalism. A procedure for detecting small-sized details in mammo- grams, based on a multifractal approach, is proposed. These details can represent microcalcifications, possi- ble signs of breast cancer. We present and discuss the results obtained using the proposed extraction method. Furthermore, we demonstrate its accuracy when applied to clinical mammograms, revealing microcalcification regions, distinguished by direct singularity information extraction.
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