Two graph theory based methods for identifying the pectoral muscle in mammograms

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    73 Citations (Scopus)

    Abstract

    Two image segmentation methods based on graph theory are used in conjunction with active contours to segment the pectoral muscle in screening mammograms. One method is based on adaptive pyramids (AP) and the other is based on minimum spanning trees (MST). The algorithms are tested on a public data set of mammograms and results are compared with previously reported methods. In 80% of the images, the boundary of the segmented regions has average error less than 2 mm. In 82 of 84 images, the boundary of the pectoral muscle found by the AP algorithm has average error less than 5 mm.
    Original languageEnglish
    Pages (from-to)2592-2602
    Number of pages11
    JournalPattern Recognition
    Volume40
    Issue number9
    DOIs
    Publication statusPublished - 2007

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