New Type-2 Fuzzy Logic Algorithm Based Image Segmentation for Medical Imaging Applications

Medical image segmentation is a plan that has a lot of potential. The achievement of automated picture segmentation makes it simple to gather biomedical and anatomical information. In terms of the subject, more study and work have increased efficacy. In the field of image processing, this work provides a type-2 fuzzy system-based image application. Computer aided diagnosis and medical image analysis both heavily rely on segmentation. This study presents a fuzzy type 2 algorithm based automated threshold selection method for the division of therapeutic pictures. It has been established that fuzzy set theory may be an effective tool for recitation surroundings when the facts are unclear or inaccurate. The algorithms have been put into practice and evaluated using brain MRI (magnetic resonance imaging) images. The outcomes have been evaluated and documented. The comparison of the controller’s efficiency of CNN has 92%.