Decision Support System Based on DCT Texture Features for Diagnosis of Esophagitis

Abstract

Esophagitis is essentially inflammation of the esophageal squamous mucosa. One of the major reasons for cause of Esophagitis is the acid reflux from the stomach. This condition is observed in the process of upper gastro-intestinal tract endoscopy and the diagnosis is arrived at by examining the images of the esophagus. The diagnosis is based on the observation of the lesions and coloration of the digestive mucosa. Our paper reports an implementation of Decision Support System (DSS) for diagnosis of Esophagitis based on the analysis of color and texture features of the images captured during the process of endoscopy. The Hue Saturation and Intensity color model is adapted. The statistical features of the Hue and Saturation form the color features and the texture features are determined by Discrete Cosine Transform coefficients of the image. The decision making structure is a feed forward neural network. The DSS has been tested and results are reported.

Mining textural knowledge in biological images: Applications, methods and trends

“…The coefficients of the transforms provide a compact representation of the original image where the most discriminative patterns are emphasised. In literature, they are widely used as texture descriptors, either as they are, or in the form of statistical features or coefficient histograms [70]. However, this approach is generally renowned for suffering from lack of spatial localisation.…”