| Literature DB >> 21669471 |
Indra Kanta Maitra1, Sanjay Nag, Samir Kumar Bandyopadhyay.
Abstract
Digital mammogram has emerged as the most popular screening technique for early detection of breast cancer and other abnormalities in human breast tissue. It provides us opportunities to develop algorithms for computer aided detection (CAD). In this paper we have proposed three distinct steps. The initial step involves contrast enhancement by using the contrast limited adaptive histogram equalization (CLAHE) technique. Then define the rectangle to isolate the pectoral muscle from the region of interest (ROI) and finally suppress the pectoral muscle using our proposed modified seeded region growing (SRG) algorithm. The proposed algorithms were extensively applied on all the 322 mammogram images in MIAS database resulting in complete pectoral muscle suppression in most of the images. Our proposed algorithm is compared with other segmentation methods showing superior results in comparison.Entities:
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Year: 2011 PMID: 21669471 DOI: 10.1016/j.cmpb.2011.05.007
Source DB: PubMed Journal: Comput Methods Programs Biomed ISSN: 0169-2607 Impact factor: 5.428