Paper
9 May 2002 Connective tissue representation for detection of microcalcifications in digital mammograms
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Abstract
Microcalcification clusters appear as an early sign of breast cancer and play an important role in interpreting mammograms. Progress is reported towards an automated computer aided detection system for clustered microcalcifications utilizing two image feature parameters: local contrast and shape. The use of a shape parameter is necessary to distinguish thin patches of connective tissue from microcalcifications. Two shape parameter techniques are compared in the segmentation of 15 digital mammogram images. The first technique implements the linear Hough transform, while the second uses image phase information in the Fourier domain. In both cases labeling of the image is performed by a deterministic relaxation scheme, in which both image data dn prior beliefs are weighted simultaneously. Similar segmentation results are obtained for each shape parameter technique however the execution time for the phase method is approximately one quarter that for the Hough method. Both techniques offer an improvement over segmentation results obtained without the shape parameter.
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Kristin Jane McLoughlin, Philip J. Bones, and Peter Kovesi "Connective tissue representation for detection of microcalcifications in digital mammograms", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467084
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Cited by 5 scholarly publications.
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KEYWORDS
Mammography

Image segmentation

Connective tissue

Electronic filtering

Digital imaging

Breast cancer

Computer aided diagnosis and therapy

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