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Related Experiment Videos

Computerized nipple identification for multiple image analysis in computer-aided diagnosis.

Chuan Zhou1, Heang-Ping Chan, Chintana Paramagul

  • 1Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109, USA. chuan@umich.edu

Medical Physics
|November 17, 2004
PubMed
Summary
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This study presents an automated method for nipple detection on mammograms, improving breast cancer diagnosis. The system accurately identifies visible nipples and reasonably estimates invisible ones, aiding computer-aided diagnosis.

Area of Science:

  • Medical Imaging
  • Radiology
  • Computer-Aided Diagnosis (CAD)

Background:

  • Mammogram correlation enhances breast cancer diagnosis accuracy.
  • Nipple location is a key landmark for aligning multiple mammograms.
  • Accurate nipple identification is challenging due to image quality and projection variations, often making nipples nearly invisible.

Purpose of the Study:

  • To develop a computerized method for automatic nipple location identification on digitized mammograms.
  • To improve the reliability of nipple detection for multi-view mammogram analysis.

Main Methods:

  • Breast boundary extraction using gradient-based tracking.
  • Geometric convergence analysis to define nipple search regions.
  • A two-stage detection method utilizing gray level, shape, and texture features.

Related Experiment Videos

  • Rule-based confidence analysis for final nipple location determination.

    • Main Results:

    • The algorithm detected 89.37% of visible nipples and 69.74% of invisible nipples within 1 cm of the gold standard in the training set.
    • In the test set, 92.28% of visible nipples and 53.62% of invisible nipples were detected within 1 cm.
    • High accuracy was achieved for visible nipples, with reasonable estimation for invisible ones.

    Conclusions:

    • Automated nipple detection is feasible and accurate on digitized mammograms.
    • This method enhances the potential for automated analysis of multiple mammograms.
    • Automated nipple detection is a crucial step towards advancing computer-aided diagnosis systems.