International Journal Of Imaging

Abstract

Brain Tumor MRI Detction and Diagnosis using Deep Learning

Author: M.Bindhiya,M.DeyDeepya,M.Pundarikaksha,GoskiSathish

Abstract:

The Brain tumor detection and diagnosis are crucial areas of medical research, as early misdiagnosis or delayed detection can have severe consequences for patient health. Our research aims to enhance the accuracy and speed of brain tumor detection using deep learning techniques applied to MRI scans. Early identification of brain tumors significantlyincreasestreatment success,butexistingmethodsstillface challenges, such as variability in image interpretation. We analyzed factorssuchaspatientdemographics,tumorcharacteristics,MRIscan attributes, medical expertise, and external elements like hospital facilitiesandtreatmentplans.Variousdeeplearningmodels,including CNN (Convolutional Neural Networks), Random Forest, SVM (Support Vector Machine), XGBoost, and RNN (Recurrent Neural Networks),wereexplored.Usinga comprehensivedataset,weassessed the effectiveness of these models in predicting both the presence and type of brain tumors. The XGBoost Classifier emerged as the most acc