Multi-Classification of Brain Tumor MRI Images Using Deep Convolutional Neural Network with Fully Optimized Framework

ABSTRACT: Brain tumor diagnosis and classification still rely on histopathological analysis of biopsy specimens today. The current method is invasive, time-consuming and prone to manual errors. These disadvantages show how essential it is to perform a fully automated method for multi-classification of brain tumors based on deep learning. This paper aims to make multi-classification of brain tumors for the early diagnosis purposes using convolutional neural network (CNN). Three different CNN models are proposed for three different classification tasks. Brain tumor detection is achieved with 99.33% accuracy using the first CNN model. The second CNN model can classify the brain tumor into five brain tumor types as normal, glioma, meningioma, pituitary and metastatic with an accuracy of 92.66%. The thir

SUBMITTER: Irmak E 

PROVIDER: S-EPMC8061452 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature