Automated detection of breast tumors using the asymmetry approach
Computers and Biomedical Research
Automated detection and classification of breast tumors
Computers and Biomedical Research
Cue generation and combination for mammographic screening
Visual search 2
Graphical Models and Image Processing
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Segmentation of the Breast Region in Mammograms Using Snakes
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Breast segmentation with pectoral muscle suppression on digital mammograms
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Coherence of multiscale features for enhancement of digital mammograms
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Image Processing
Fully automated gradient based breast boundary detection for digitized X-ray mammograms
Computers in Biology and Medicine
Pectoral muscle segmentation: A review
Computer Methods and Programs in Biomedicine
Breast mass contour segmentation algorithm in digital mammograms
Computer Methods and Programs in Biomedicine
Expert Systems with Applications: An International Journal
Saliency based mass detection from screening mammograms
Signal Processing
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This paper presents a novel method for the segmentation of regions of interest in mammograms. The algorithm concurrently delineates the boundaries of the breast boundary, the pectoral muscle, as well as dense regions that include candidate masses. The resulting representation constitutes an analysis of the global structure of the object in the mammogram. We propose a topographic representation called the isocontour map, in which a salient region forms a dense quasi-concentric pattern of contours. The topological and geometrical structure of the image is analyzed using an inclusion tree that is a hierarchical representation of the enclosure relationships between contours. The "saliency" of a region is measured topologically as the minimum nesting depth. Features at various scales are analyzed in multiscale isocontour maps, and we demonstrate that the multiscale scheme provides an efficient way of achieving better delineations. Experimental results demonstrate that the proposed method has potential as the basis for a prompting system in mammogram mass detection.