Classification of dermatological ulcers based on tissue composition and color texture features

Authors:
Silvio Moreto Pereira;Marco Andrey Cipriani Frade;Rangaraj Mandayam Rangayyan;Paulo Mazzoncini de Azevedo Marques
Affiliations:
EESC, University of São Paulo, São Carlos, Brazil;EESC, University of São Paulo, São Carlos, Brazil;University of Calgary, Calgary, Canada;University of São Paulo, Ribeirão Preto, Brazil
Venue:
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Year:
2011

Citing 11
Cited 0

Induction of fuzzy decision trees

Fuzzy Sets and Systems
Overfitting and undercomputing in machine learning

ACM Computing Surveys (CSUR)
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss

Machine Learning - Special issue on learning with probabilistic representations
Machine learning in automated text categorization

ACM Computing Surveys (CSUR)
When Is ''Nearest Neighbor'' Meaningful?

ICDT '99 Proceedings of the 7th International Conference on Database Theory
Digital Image Processing (3rd Edition)

Digital Image Processing (3rd Edition)
A study of cross-validation and bootstrap for accuracy estimation and model selection

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The WEKA data mining software: an update

ACM SIGKDD Explorations Newsletter
A Theoretical Comparison of Texture Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
A query-by-example content-based image retrieval system of non-melanoma skin lesions

MCBR-CDS'09 Proceedings of the First MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images

IEEE Transactions on Information Technology in Biomedicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present color image processing methods for the analysis of images of dermatological lesions. The intended application is classification and analysis of the tissue composition of skin lesions or ulcers, in terms of granulation (red), fibrin (yellow), necrotic (black), callous (white), and mixed tissue composition. The images were analyzed and classified by an expert dermatologist into the classes mentioned above. Indexing of the images was performed based on statistical texture features derived from cooccurrence matrices of the RGB, HSV, L*a*b*, and L*u*v* color components. The classification was performed using different classifiers and database organization methods. The performance of classification was measured in terms of the area under the receiver operating characteristic curve, with values of up to 0.98 for the granulation and fibrin classes.