Identification of variegated coloring in skin tumors: neural network vs. rule-based induction methods

Author

Durg, Ajaya ; Stoecker, William Aiaya V ; Cookson, John P. ; Umbaugh, S.E. ; Moss, Randy H.

Author_Institution

Missouri Univ., Rolla, MO, USA

Volume

12

Issue

3

fYear

1993

Firstpage

71

Lastpage

74

Abstract

The use of neural networks for automatic identification of variegated coloring, which is believed to be one of the most predictive features for malignant melanoma, is described. The Nestor development system (NDS) was chosen for neural network implementation. At the heart of NDS is a three-layer neural network called a restricted Coulomb energy (RCE) network. The learning scheme and the database for detection of variegated coloring are discussed. Results are reported.<>

Keywords

colour; medical image processing; neural nets; skin; 3-layer neural network; Nestor development system; database; learning scheme; malignant melanoma predictive features; medical diagnosis; restricted Coulomb energy network; rule-based induction methods; variegated coloring identification; Artificial neural networks; Biological neural networks; Cancer; Decision trees; Humans; Intelligent networks; Malignant tumors; Neural networks; Neurons; Skin neoplasms;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.232345

Filename

232345