Paper Info
Title
An efficient pixel value based mapping scheme to delineate pectoral muscle from mammograms
Abstract
Mammograms are X-ray images which are used in breast cancer detection. In Computer Aided Detection of breast cancer from digital mammogram, elimination of pectoral muscle is a very important and challenging issue. This is because of the fact that pectoral muscle in mediolateral oblique (MLO) mammogram images has common photographic properties with suspicious mass and micro-calcification. Presence of pectoral muscle gives false positive result in automated breast cancer detection. In this paper a novel and efficient method using pixel value mapping is proposed to delineate pectoral muscle region accurately. The proposed method is capable of segmenting pectoral muscle of a broad range of size, shape and position. This algorithm is found to be robust not only to large variations of size, shape and positions of pectoral muscle, but also to any kind of artifacts like medical tags. The algorithm has been applied to 322 images of Mammographic Image Analysis Society (MIAS) database. The segmented results were then evaluated by two expert radiologists, who rated 84% and 94% of the segmentations to be accurate respectively. This algorithm is found to be robust not only to large variations of size, shape and positions of pectoral muscle, but also to any kind of artifacts like medical tags.
Year
DOI
Venue
2010
10.1109/BICTA.2010.5645272
BIC-TA
Keywords
Field
DocType
breast cancer,muscle,region growing,accuracy,databases,false positive,image segmentation,cancer
Computer vision,Mammography,Microcalcification,Computer science,Computer aided detection,Image segmentation,Pectoral muscle,Digital mammogram,Artificial intelligence,Pixel,False-positive result
Conference
ISBN
Citations 
PageRank 
978-1-4244-6437-1
2
0.37
References 
Authors
4
3
Name
Order
Citations
PageRank
Saltanat, N.120.37
M. Alamgir Hossain210716.52
Mohammad S. Alam37911.10