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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Computer-aided diagnostic models in breast cancer screening.

Turgay Ayer1, Mehmet Us Ayvaci, Ze Xiu Liu

  • 1Industrial & Systems Engineering Department, University of Wisconsin, Madison, WI, USA.

Imaging in Medicine
|September 14, 2010
PubMed
Summary

This review surveys computer-aided diagnostic (CADx) models for breast cancer detection using mammography, ultrasound, and MRI. It highlights CADx model types, data, and performance, identifying future research directions for improved accuracy.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence in Healthcare

Background:

  • Mammography, ultrasound, and MRI are key for breast cancer detection.
  • Distinguishing early cancer signs from normal structures in these images is challenging.
  • Computer-aided detection and diagnostic (CADx) models assist physicians.

Purpose of the Study:

  • To comprehensively survey CADx models for mammography, ultrasound, and MRI interpretation.
  • To summarize key aspects of published CADx studies.
  • To identify limitations and future research directions in CADx for breast imaging.

Main Methods:

  • Systematic review of CADx models in breast imaging over the past 20 years.
  • Categorization of studies by imaging modality (mammography, ultrasound, MRI).

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  • Analysis of model type, data characteristics, feature selection, and performance metrics.

    • Main Results:

    • Detailed summary of numerous CADx studies across different modalities.
    • Description of various computer models, input data, and feature types used.
    • Compilation of performance measures for evaluated CADx models.

    Conclusions:

    • Existing CADx models show promise but have limitations.
    • Further research is needed to enhance CADx model accuracy and clinical utility.
    • Future directions include addressing data limitations and improving model generalizability.