Classification of Confocal Laser Endomicroscopic Images of the Oral Cavity to Distinguish Pathological from Healthy Tissue
Confocal laser endomicroscopy is a recently introduced advanced imaging technique which enables microscopic imaging of the mucosa in-vivo. This technique has already been applied successfully during diagnosis of gastrointestinal diseases. Whereas for this purpose several computer aided diagnosis approaches exist, we present a classification system that is able to differentiate between healthy and pathological images of the oral cavity. Varying textural features of small rectangular regions are evaluated using random forests and support vector machines. Preliminary results reach up to 99.2% classification rate. This indicates that an automatic classification system to differentiate between healthy and pathological mucosa of the oral cavity is feasible.
KeywordsSupport Vector Machine Oral Cavity Random Forest Local Binary Pattern Average Recall
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