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Updated: Jun 18, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Published on: August 30, 2013

Mass auto-detection in mammogram based on wavelet transform modulus maximum.

Li Ke1, Wei He, Yan Kang

  • 1Institute of Biomedical and Electromagnetic Engineering, Shenyang University of Technology, Shenyang, Liaoning, China. amykeli@hotmail.com

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
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This study introduces a new method using Wavelet Transform Modulus Maximum (WTMM) to improve mass detection in mammograms. The technique enhances computer-aided diagnosis (CAD) systems for more accurate cancer screening.

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Signal Processing

Background:

  • Accurate detection of masses in mammograms is crucial for effective computer-aided diagnosis (CAD).
  • Existing CAD systems face challenges in detecting masses, especially those connected to surrounding tissues.
  • Improving mass detection accuracy directly impacts diagnostic performance and patient outcomes.

Purpose of the Study:

  • To propose a novel approach for enhancing mass detection in mammograms.
  • To improve the accuracy and efficiency of computer-aided diagnosis (CAD) systems.
  • To effectively detect both isolated and complex mass structures in mammographic images.

Main Methods:

  • The proposed method utilizes Wavelet Transform Modulus Maximum (WTMM) for enhanced mass detection.

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  • Regions of Interest (ROIs) are initially identified using a multi-thresholding technique.
  • The contour of the ROI is extracted from the modulus image obtained via WTMM for precise localization.

    • Main Results:

    • The WTMM-based approach successfully detects isolated masses in mammograms.
    • The method demonstrates efficacy in identifying masses connected to glandular tissues.
    • Experimental results confirm the potential for improved performance in CAD systems.

    Conclusions:

    • The novel WTMM approach significantly enhances mass detection accuracy in mammograms.
    • This technique offers a promising solution for improving CAD system performance.
    • The method's ability to detect complex mass presentations could lead to better diagnostic accuracy.