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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Automated detection and enhancement of microcalcifications in mammograms using nonlinear subband decomposition

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      Author
      Ansari, R.
      Gürcan, M. Nafi
      Yardımcı, Yasemin
      Çetin, A. Enis
      Date
      1997
      Source Title
      Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, IEEE 1997
      Print ISSN
      0736-7791
      Publisher
      IEEE
      Pages
      3069 - 3072
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      In this paper, computer-aided detection and enhancement of microcalcifications in mammogram images are considered. The mammogram image is first decomposed into subimages using a `subband' decomposition filter bank which uses nonlinear filters. A suitably identified subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. All regions with high positive skewness and kurtosis are marked as a regions of interest. Next, an outlier labeling method is used to find the locations of microcalcifications in these regions. An enhanced mammogram image is also obtained by emphasizing the microcalcification locations. Linear and nonlinear subband decomposition structures are compared in terms of their effectiveness in finding microcalcificated regions and their computational complexity. Simulation studies based on real mammogram images are presented.
      Keywords
      Calcification (biochemistry)
      Computational complexity
      Computer simulation
      Image enhancement
      Image segmentation
      Medical imaging
      Mammogram images
      Microcalcification
      Nonlinear subband decomposition
      Pattern recognition
      Permalink
      http://hdl.handle.net/11693/27708
      Published Version (Please cite this version)
      https://doi.org/10.1109/ICASSP.1997.595440
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      • Department of Electrical and Electronics Engineering 3524
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