Purpose: To explore texture features in two-dimensional images to differentiate seborrheic keratosis from melanoma.
Methods: A systematic approach to consistent classification of skin tumors is described. Texture features, based on the second-order histogram, were used to identify the features or a combination of features that could consistently differentiate a malignant skin tumor (melanoma) from a benign one (seborrheic keratosis). Two hundred and seventy-one skin tumor images were separated into training and test sets for accuracy and consistency. Automatic induction was applied to generate classification rules. Data analysis and modeling tools were used to gain further insight into the feature space.
Result and Conclusions: In all, 85-90% of seborrheic keratosis images were correctly differentiated from the malignant skin tumors. The features correlation_average, correlation_range, texture_energy_average and texture_energy_range were found to be the most important features in differentiating seborrheic keratosis from melanoma. Overall, the seborrheic keratosis images were better identified by the texture features than the melanoma images.
S. V. Deshabhoina et al., "Melanoma and Seborrheic Keratosis Differentiation using Texture Features," Skin Research and Technology, vol. 9, no. 4, pp. 348-356, John Wiley & Sons, Nov 2003.
The definitive version is available at http://dx.doi.org/10.1034/j.1600-0846.2003.00044.x
Electrical and Computer Engineering
National Institutes of Health (U.S.). Small Business Innovation Research Program
Stoecker and Associates
Keywords and Phrases
Accuracy; Article; Controlled Study; Data Analysis; Histogram; Image Analysis; Melanoma; Seborrheic Keratosis; Skin Tumor; Statistical Model; Tumor Classification; Diagnosis, Differential; Humans; Image Processing, Computer-Assisted; Keratosis, Seborrheic; Reproducibility Of Results; Skin Neoplasms; Classification Rules; Computer Vision; Second-Order Histogram Features; Texture Analysis
International Standard Serial Number (ISSN)
Article - Journal
© 2003 John Wiley & Sons, All rights reserved.