Abstract
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.
Recommended Citation
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 https://doi.org/10.1034/j.1600-0846.2003.00044.x
Department(s)
Chemistry
Second Department
Electrical and Computer Engineering
Sponsor(s)
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)
0909-752X; 1600-0846
Document Type
Article - Journal
Document Version
Accepted Manuscript
File Type
text
Language(s)
English
Rights
© 2003 John Wiley & Sons, All rights reserved.
Publication Date
01 Nov 2003
PubMed ID
14641886
Comments
This research was funded in part by an SBIR Phase II grant from the National Institutes of Health through a subcontract from Stoecker and Associates, Rolla, Missouri, USA, SIUE account #2-70252.
This is the peer reviewed version of the following article: Melanoma and Seborrheic Keratosis Differentiation using Texture Features, which has been published in final form at http://dx.doi.org/10.1034/j.1600-0846.2003.00044.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.