A non-linear morphometric feature selection approach for breast tumor contour from ultrasonic images

  • Authors:

  • Wagner Coelho A. Pereira;André V. Alvarenga;Antonio Fernando C. Infantosi;Leonardo Macrini;Carlos E. Pedreira

  • Affiliations:

  • Biomedical Engineering Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-972, Brazil;Laboratory of Ultrasound - National Institute of Metrology, Standardization and Industrial Quality (Inmetro), Rio de Janeiro 25250-020, Brazil;Biomedical Engineering Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-972, Brazil;Economy and Accurate Sciences Department, Rural Federal University of Rio de Janeiro, Rio de Janeiro 23851-970, Brazil;School of Medicine and COPPE-PEE-Engineering Graduate Program/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2010

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Abstract

Ultrasound breast images have been used to improve diagnostics and decrease the number of unneeded biopsies. Malignant breast tumors tend to present irregular and blurred contours while benign ones are usually round, smooth and well-defined. Accordingly, investigating the tumor contour may help in establishing diagnosis. Herein, Mutual Information and Linear Discriminant Analysis were implemented to rank morphometric features in discriminating breast tumors in ultrasound images. Seven features were extracted from Convex Polygon and the Normalized Radial Length techniques. By applying a Mutual Information based approach, it was possible to identity features with possibly non-linear contributions to the outcome.