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Related Experiment Video

Updated: Jul 8, 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

Tree-structured nonlinear filters in digital mammography.

W Qian1, L P Clarke, M Kallergi

  • 1Dept. of Radiol., Univ. of South Florida, Tampa, FL.

IEEE Transactions on Medical Imaging
|January 1, 1994
PubMed
Summary
This summary is machine-generated.

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A novel nonlinear filter enhances digital mammography by improving noise suppression and detail preservation. This new algorithm offers better edge detection, aiding computer-assisted diagnosis in mammography.

Area of Science:

  • Medical Imaging
  • Image Processing
  • Biomedical Engineering

Background:

  • Digital mammography is crucial for breast cancer screening.
  • Effective noise suppression and detail preservation are vital for accurate diagnosis.
  • Existing filters may struggle to balance noise reduction with maintaining image fidelity.

Purpose of the Study:

  • To propose a new class of nonlinear filters for digital mammography.
  • To enhance noise suppression and detail preservation in mammographic images.
  • To improve edge detection capabilities for computer-assisted diagnosis.

Main Methods:

  • A multistage tree-structured filter using central weighted median filters.
  • A dispersion edge detector integrated into the algorithm.

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Last Updated: Jul 8, 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

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Pulmonary Structural MRI using Free-Breathing, Self-Gated Ultra-short Echo Time Imaging

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  • Evaluation using simulated and real mammographic images with variable shape windows.

    • Main Results:

    • The proposed filter demonstrated superior noise suppression compared to single filters.
    • The algorithm showed improved detail preservation and edge detection.
    • Expert mammographer evaluation confirmed the filter's effectiveness on malignancy-containing images.

    Conclusions:

    • The new nonlinear filter offers robust performance for digital mammography.
    • It provides better detail preservation, noise suppression, and edge detection.
    • The filter shows potential as a valuable tool for computer-assisted diagnosis in mammography.