Automatic recognition of spicules in mammograms

  • Hao Jiang
  • Wilson Tiu
  • Shinji Yamamoto
  • Shun-ichi Iisaku
Poster Session D: Biomedical Applications, Detection, Control & Surveillance, Inspection, Optical Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)


This paper presents a method of automatic recognition of spicules in mammograms. The method is consisted of two steps, enhancement and feature selection. First, spicule shadows are enhanced by using a newly developed operation. An opening operation is applied to remove noises and a direction map is made for feature selection. Second, a concentration expression is given with gray levels and two features are selected for recognition of tumors with spicules. In the method, the direction of spicules is not only considered, but the density is also utilized. The method was tested on 24 samples including seven tumors with spicules. The recognition rate for tumors with spicules was 100% without the false positives.


Feature Selection Original Image Gray Level Compute Radiography Seed Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Hao Jiang
    • 1
  • Wilson Tiu
    • 2
  • Shinji Yamamoto
    • 2
  • Shun-ichi Iisaku
    • 1
  1. 1.Communications Research Laboratory, MPTKoganei, TokyoJapan
  2. 2.Toyohashi University of TechnologyToyohashi, AichiJapan

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