Applying artificial intelligence to the identification of variegated coloring in skin tumors

Author

Umbaugh, S.E. ; Moss, R.H. ; Stoecker, W.V.

Author_Institution

Dept. of Electr. Eng., Southern Illinois Univ., Edwardsville, IL, USA

Volume

10

Issue

4

fYear

1991

Firstpage

57

Lastpage

62

Abstract

The importance of color information for the automatic diagnosis of skin tumors by computer vision is demonstrated. The utility of the relative color concept is proved by the results in identifying variegated coloring. A feature file paradigm is shown to provide an effective methodology for the independent development of software modules for expert system/computer vision research. An automatic induction tool is used effectively to generate rules for identifying variegated coloring. Variegated coloring can be identified at rates as high as 92% when using the automatic induction technique in conjunction with the color segmentation method.<>

Keywords

artificial intelligence; computer vision; expert systems; medical diagnostic computing; skin; artificial intelligence; automatic diagnosis; automatic induction tool; color information; color segmentation method; computer vision; expert system; feature file paradigm; skin tumors; software modules; variegated coloring identification; Artificial intelligence; Cancer; Classification algorithms; Decision trees; Expert systems; Humans; Induction generators; Neural networks; Skin neoplasms; Virtual colonoscopy;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.107171

Filename

107171