21 May 1999 Oral lesion classification using true-color images
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Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999); doi: 10.1117/12.348507
Event: Medical Imaging '99, 1999, San Diego, CA, United States
Abstract
The aim of the study was to investigate effective image analysis methods for the discrimination of two oral lesions, oral lichenoid reactions and oral leukoplakia, using only color information. Five different color representations (RGB, Irg, HSI, I1I2I3 and La*b*) were studied and their use for color analysis of mucosal images evaluated. Four common classifiers (Fisher's linear discriminant, Gaussian quadratic, kNN-Nearest Neighbor and Multilayer Perceptron) were chosen for the evaluation of classification performance. The feature vector consisted of the mean color difference between abnormal and normal regions extracted from digital color images. Classification accuracy was estimated using resubstitution and 5-fold crossvalidation methods. The best classification results were achieved in HSI color system and using linear discriminant function. In total, 70 out of 74 (94.6%) lichenoid reactions and 14 out of 20 (70.0%) of leukoplakia were correctly classified using only color information.
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Artur Chodorowski, Ulf Mattsson, Tomas Gustavsson, "Oral lesion classification using true-color images", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348507; https://doi.org/10.1117/12.348507
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KEYWORDS
RGB color model

Error analysis

Classification systems

Image analysis

Cancer

Color difference

Computing systems

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