A Fuzzy-Based Histogram Analysis Technique for Skin Lesion Discrimination in Dermatology Clinical Images

Abstract

A fuzzy logic-based color histogram analysis technique is presented for discriminating benign skin lesions from malignant melanomas in dermatology clinical images. The approach utilizes a fuzzy set for benign skin lesion color, and alpha-cut and support set cardinality for quantifying a fuzzy ratio skin lesion color feature. Skin lesion discrimination results are reported for the fuzzy ratio and fusion with a previously determined percent melanoma color feature over a data set of 258 clinical images. For the fusion technique, alpha-cuts for the fuzzy ratio can be chosen to recognize over 93.30% of melanomas with approximately 15.67% false positive lesions.

Department(s)

Electrical and Computer Engineering

Second Department

Chemistry

Keywords and Phrases

Approximation Theory; Algorithms; Benign Tumor; Clinical Feature; Color Histogram Analysis; Computer Assisted Diagnosis; Dermatology; Diagnosis; Diagnostic Accuracy; Diagnostic Imaging; Diagnostic Value; Differential Diagnosis; Fuzzy Logic; Fuzzy Sets; Humans; Image Analysis; Malignant Melanoma; Medical Imaging; Model; Priority Journal; Skin Defect; Skin Neoplasms; Skin Pigmentation; Skin Tumor

International Standard Serial Number (ISSN)

0895-6111

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2003 Elsevier, All rights reserved.

Publication Date

01 Sep 2003

Link to Full Text

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