Computer-aided diagnosis in clinical endoscopy using neuro-fuzzy systems

An innovative detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the new M2A swallowable imaging capsule - a patented, video colour-imaging disposable capsule. Schemes have been developed to extract new texture features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The detection accuracy of the proposed system has reached to 100%, providing thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.