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Related Experiment Video

Updated: Jun 1, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Technique for preprocessing of digital mammogram.

Indra Kanta Maitra1, Sanjay Nag, Samir Kumar Bandyopadhyay

  • 1Department of Computer Science & Engineering, University of Calcutta, Kolkata, West Bengal, India. ikm.1975@yahoo.com

Computer Methods and Programs in Biomedicine
|June 15, 2011
PubMed
Summary

This study introduces a novel computer-aided detection (CAD) algorithm for digital mammograms. The method effectively suppresses pectoral muscles, improving breast cancer screening accuracy.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Computer Vision

Background:

  • Digital mammography is crucial for early breast cancer detection.
  • Computer-aided detection (CAD) algorithms enhance diagnostic accuracy.
  • Pectoral muscle segmentation is a challenge in mammogram analysis.

Purpose of the Study:

  • To develop and evaluate a novel algorithm for pectoral muscle suppression in digital mammograms.
  • To improve the region of interest (ROI) for subsequent computer-aided detection (CAD) analysis.
  • To enhance the effectiveness of breast cancer screening techniques.

Main Methods:

  • Contrast enhancement using Contrast Limited Adaptive Histogram Equalization (CLAHE).
  • Pectoral muscle isolation using a defined rectangular region.

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Last Updated: Jun 1, 2026

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  • Pectoral muscle suppression via a modified seeded region growing (SRG) algorithm.

    • Main Results:

    • The proposed algorithm was applied to 322 mammograms from the MIAS database.
    • Complete pectoral muscle suppression was achieved in most images.
    • The algorithm demonstrated superior performance compared to existing segmentation methods.

    Conclusions:

    • The developed algorithm effectively suppresses pectoral muscles in digital mammograms.
    • This technique can significantly improve the quality of ROI for CAD systems.
    • The findings suggest a potential advancement in automated breast cancer screening.