Brain Tumor Detection Using RNN

DOI

https://www.doi.org/10.59256/ijire.2023040396

Published In

Volume 4, Issue 3 (2023)

Published Online

May-June 2023

Pages

338-341

Article Type

Research Article

Check for updates

Abstract: 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,via progressingintheimageprocessing,different methodologies 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 the brain is suggested utilizing MR Iimages. Such method includes various procedures of image processing, like filtering, the removal of noise,segmentation,and morphologicalprocesses. 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.