Texture analysis of ultrasonic images using backpropagation neural networks

Poster Session
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)


Backpropagation neural networks are applied to the problem of characterization of ultrasonic image texture to detect abnormalities in tissue texture which are indicative of liver disease. Twenty-one texture features were extracted from regions of interest in digitized ultrasonic images. A feature subset, identified by a stepwise selection process, formed the sample input to the networks together with the physician-supplied diagnosis. The classification performance of the backpropagation network is evaluated using a jackknife testing procedure. The performance of the networks is compared with results obtained from linear discriminant analysis and logistic regression techniques.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Jo Ann Parikh
    • 2
  • John DaPonte
    • 2
  • Meledath Damodaran
    • 1
  1. 1.University of Houston - VictoriaVictoriaUSA
  2. 2.Southern Connecticut State UniversityNew HavenUSA

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