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

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

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 indep...

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Bibliographic Details
Published in:IEEE engineering in medicine and biology magazine Vol. 10; no. 4; pp. 57 - 62
Main Authors: Umbaugh, S.E., Moss, R.H., Stoecker, W.V.
Format: Journal Article
Language:English
Published: United States IEEE 01-12-1991
Subjects:
Artificial intelligence
Cancer
Classification algorithms
Decision trees
Expert systems
Humans
Induction generators
Neural networks
Skin neoplasms
Virtual colonoscopy
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Summary: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.< >
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ISSN:0739-5175
DOI:10.1109/51.107171