Brain Tumor Detection Using RNN

This research work aims to utilize the developed and evaluated Magnetic Resonance Imaging(MRI) technique for the classification of brain tumor and seizures employing Recurrent Neural Network (RNN). The medical science in the image processing is an emergent area that has suggested many progressive methods in detecting as well as analyzing a specific disease. Brain tumors treatment is recently getting progressively more challenging owing to the intricate shape,structureandthetextureoftumor.So,viaprogressingintheimageprocessing,differentmethodologies have been suggested for identifying the tumors inside brain. The progression in such area made a need for searching more upon the methods and approaches evolved for the extraction of tumor. Therefore, an extraction system the tumor from thebrainissuggestedutilizingMRIimages.Suchmethodincludesvariousproceduresofimageprocessing,likefiltering,theremovalofnoise,segmentation,andmorphologicalprocesses. Brain tumor extraction can be successfully achieved via conducting such processes upon. The cross-correlation is calculated between the changeable vector of a target and the zone of tumor for determining in what way the values of people of the zone of tumor are narrowly, associated utilizing the image processing and the RNN method accomplishing 99.71%accuracy. Key Word: Brain RNN, Image processing, Image segmentation, Feature extraction, Image classification