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Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography.

Publication ,  Journal Article
Mazurowski, MA; Habas, PA; Zurada, JM; Tourassi, GD
Published in: Phys Med Biol
February 21, 2008

This paper presents an optimization framework for improving case-based computer-aided decision (CB-CAD) systems. The underlying hypothesis of the study is that each example in the knowledge database of a medical decision support system has different importance in the decision making process. A new decision algorithm incorporating an importance weight for each example is proposed to account for these differences. The search for the best set of importance weights is defined as an optimization problem and a genetic algorithm is employed to solve it. The optimization process is tailored to maximize the system's performance according to clinically relevant evaluation criteria. The study was performed using a CAD system developed for the classification of regions of interests (ROIs) in mammograms as depicting masses or normal tissue. The system was constructed and evaluated using a dataset of ROIs extracted from the Digital Database for Screening Mammography (DDSM). Experimental results show that, according to receiver operator characteristic (ROC) analysis, the proposed method significantly improves the overall performance of the CAD system as well as its average specificity for high breast mass detection rates.

Duke Scholars

Published In

Phys Med Biol

DOI

ISSN

0031-9155

Publication Date

February 21, 2008

Volume

53

Issue

4

Start / End Page

895 / 908

Location

England

Related Subject Headings

  • ROC Curve
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Diagnosis, Computer-Assisted
  • Decision Support Systems, Clinical
  • Databases, Factual
  • Case-Control Studies
  • Algorithms
  • 5105 Medical and biological physics
  • 1103 Clinical Sciences
 

Citation

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Mazurowski, M. A., Habas, P. A., Zurada, J. M., & Tourassi, G. D. (2008). Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography. Phys Med Biol, 53(4), 895–908. https://doi.org/10.1088/0031-9155/53/4/005
Mazurowski, Maciej A., Piotr A. Habas, Jacek M. Zurada, and Georgia D. Tourassi. “Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography.Phys Med Biol 53, no. 4 (February 21, 2008): 895–908. https://doi.org/10.1088/0031-9155/53/4/005.
Mazurowski MA, Habas PA, Zurada JM, Tourassi GD. Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography. Phys Med Biol. 2008 Feb 21;53(4):895–908.
Mazurowski, Maciej A., et al. “Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography.Phys Med Biol, vol. 53, no. 4, Feb. 2008, pp. 895–908. Pubmed, doi:10.1088/0031-9155/53/4/005.
Mazurowski MA, Habas PA, Zurada JM, Tourassi GD. Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography. Phys Med Biol. 2008 Feb 21;53(4):895–908.
Journal cover image

Published In

Phys Med Biol

DOI

ISSN

0031-9155

Publication Date

February 21, 2008

Volume

53

Issue

4

Start / End Page

895 / 908

Location

England

Related Subject Headings

  • ROC Curve
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Diagnosis, Computer-Assisted
  • Decision Support Systems, Clinical
  • Databases, Factual
  • Case-Control Studies
  • Algorithms
  • 5105 Medical and biological physics
  • 1103 Clinical Sciences