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Automated Detection Method for Architectural Distortion with Spiculation Based on Distribution Assessment of Mammary Gland on Mammogram

  • Takeshi Hara
  • Takanari Makita
  • Tomoko Matsubara
  • Hiroshi Fujita
  • Yoriko Inenaga
  • Tokiko Endo
  • Takuji Iwase
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)

Abstract

The clustered microcalcifications and mass are the important findings in interpreting breast cancer, architectural distortion on mammograms as well. We have developed the detection algorithm for distorted area based on concentration of mammary gland. The purpose of this study is to suggest the improvement of extraction method of mammary gland in order to achieve higher sensitivity. The mean curvature, and the combination of shape index and curvedness were performed for extracting of mammary gland in our previous methods. In our new method, the dynamic-range compression was added as the pre-processing before extracting mammary gland by mean curvature. The detection rate at initial pick-up stage was improved by this improvement. It was concluded that our detection method would be effective.

Keywords

Mammary Gland Mammographic Density Concentration Index Shape Index Synthetic 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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Takeshi Hara
    • 1
  • Takanari Makita
    • 1
  • Tomoko Matsubara
    • 2
  • Hiroshi Fujita
    • 1
  • Yoriko Inenaga
    • 3
  • Tokiko Endo
    • 4
  • Takuji Iwase
    • 5
  1. 1.Division of Regeneration and Advanced, Graduate School of MedicineGifu UniversityGifuJapan
  2. 2.School of Information CultureNagoya Bunri UniversityAichiJapan
  3. 3.Konica Minolta Medical & Graphic, IncTokyoJapan
  4. 4.National Hospital Organization Nagoya Medical CenterAichiJapan
  5. 5.The Cancer Institute Hospital of JFCRTokyoJapan

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