Brain Tumor and Glioma Grade Classification Using Gaussian Convolutional Neural Network

Understanding brain diseases such as categorizing Brain-Tumor (BT) is critical to assess the tumors and facilitate patient with proper cure per their categorizations. Numerous imaging schemes exist for BT detection, Magnetic Resonance Imaging (MRI), generally utilized because of better quality images reality depending on non-ionizing radiation. This paper proposes an approach detect distinctive types using Gaussian Convolutional Neural Network (GCNN) two datasets. One datasets used classify into pituitary, glioma, meningioma. The other one separates three grades i.e., Grade-two, Grade-three, Grade-four. These have ’233’ ’73’ victims a total ’3064’ ’516’ T1-weighted complexity improved pictures first second datasets, separately. proposed achieves accuracy 99.8% 97.14% experimental results highlight efficiency multi-class categorization.