Fuzzy logic techniques for blotch feature evaluation in dermoscopy images

Khan, Azmath; Gupta, Kapil; Stanley, R.J.; Stoecker, William V.; Moss, Randy H.; Argenziano, Giuseppe; Soyer, H. Peter; Rabinovitz, Harold S.; Cognetta, Armand B.

doi:10.1016/j.compmedimag.2008.10.001

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Volume 33, Issue 1 , Pages 50-57, January 2009

Fuzzy logic techniques for blotch feature evaluation in dermoscopy images

Azmath Khan
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409-0040, United States
Kapil Gupta
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409-0040, United States
R.J. Stanley
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409-0040, United States
- Corresponding author. Tel.: +1 573 341 6896; fax: +1 573 341 4532.
William V. Stoecker
- Stoecker & Associates, 1702 E. 10th St., Rolla, MO 65401-4600, United States
- Division of Dermatology, Department of Internal Medicine, University of Missouri Health Sciences Center, Columbia, MO 65212, United States
Randy H. Moss
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65409-0040, United States
Giuseppe Argenziano
- Department of Dermatology, Second University of Naples, Naples, Italy
H. Peter Soyer
- Queensland Institute of Dermatology, University of Queensland, Woolloongaba, Australia
Harold S. Rabinovitz
- Skin and Cancer Associates, 201 NW 82nd Ave Ste 501, Plantation, FL 33324-1857, United States
Armand B. Cognetta
- Division of Dermatology, Department of Internal Medicine, University of Missouri Health Sciences Center, Columbia, MO 65212, United States
- Dermatology Associates, 1714 Mahan Center Blvd, Tallahassee, FL 32308, United States

Received 1 February 2008; received in revised form 21 September 2008; accepted 9 October 2008.

Abstract

Blotches, also called structureless areas, are critical in differentiating malignant melanoma from benign lesions in dermoscopy skin lesion images. In this paper, fuzzy logic techniques are investigated for the automatic detection of blotch features for malignant melanoma discrimination. Four fuzzy sets representative of blotch size and relative and absolute blotch colors are used to extract blotchy areas from a set of dermoscopy skin lesion images. Five previously reported blotch features are computed from the extracted blotches as well as four new features. Using a neural network classifier, malignant melanoma discrimination results are optimized over the range of possible alpha-cuts and compared with results using crisp blotch features. Features computed from blotches using the fuzzy logic techniques based on three plane relative color and blotch size yield the highest diagnostic accuracy of 81.2%.

Keywords: Asymmetric blotches, Dermoscopy, Fuzzy logic, Image analysis, Malignant melanoma, Neural network