| Summary: | In recent years, minimally invasive endoscopic procedures have been increasingly employed for diagnostic and surgical purposes, thus decreasing the in-hospital stay period and time for recovery of the patient. These procedures are manually performed and analysed by expert endoscopists such as in the gastrointestinal and respiratory cases. Hence these procedures are subjective and require special slulls as well as experience. Development of new algorithms and techniques for computer-based processing of the images and analyzing them to detect abnormalities will enhance the overall efficacy of the minimally invasive procedures. The present project is aimed at the design and development of an efficient endoscopic instrumentation system for abnormality detection and telediagnosis, by incorporation of intelligent modules in image acquisition, image processing, image analysis and decision-malung regarding the presence of abnormalities. This project considers networked configuration of multiple task-sites to facilitate teleconsultation. Testing is carried out on clinical endoscopic images. The results obtained generally support the feasibility of the proposed approach. The experimental results are discussed at length. Refinements are made to the proposed methods for improving the accuracy of abnormality detection. Thus, a computer-based, intelligent, minimally invasive endoscopic has been developed for efficient detection of abnormalities in the gastrointestinal system.
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