A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification of breast tissue by texture analysis
Image and Vision Computing - Special issue: BMVC 1991
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Directional Analysis of Images with Gabor Wavelets
SIBGRAPI '00 Proceedings of the 13th Brazilian Symposium on Computer Graphics and Image Processing
Two graph theory based methods for identifying the pectoral muscle in mammograms
Pattern Recognition
Proceedings of the 2007 ACM symposium on Applied computing
Breast Skin-Line Segmentation Using Contour Growing
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Computer-aided evaluation of screening mammograms based on local texture models
IEEE Transactions on Image Processing
A fully automated complete segmentation scheme for mammograms
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Fractal analysis of mammograms
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Segmentation of regions of interest in mammograms in a topographic approach
IEEE Transactions on Information Technology in Biomedicine
The use of multi-scale monogenic signal on structure orientation identification and segmentation
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Validation of graph theoretic segmentation of the pectoral muscle
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
EdgeFlow: a technique for boundary detection and image segmentation
IEEE Transactions on Image Processing
Saliency based mass detection from screening mammograms
Signal Processing
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Mammograms are X-ray images of breasts which are used to detect breast cancer. The pectoral muscle is a mass of tissue on which the breast rests. During routine mammographic screenings, in Medio-Lateral Oblique (MLO) views, the pectoral muscle turns up in the mammograms along with the breast tissues. The pectoral muscle has to be segmented from the mammogram for an effective automated Computer Aided Diagnosis (CAD). This is due to the fact that pectoral muscles have pixel intensities and texture similar to that of breast tissues which can result in awry CAD results. As a result, a lot of effort has been put into the segmentation of pectoral muscles and finding its contour with the breast tissues. To the best of our knowledge, currently there is no definitive literature available which provides a comprehensive review about the current state of research in this area of pectoral muscle segmentation. We try to address this shortcoming by providing a comprehensive review of research papers in this area. A conscious effort has been made to avoid deviating into the area of automated breast cancer detection.