Brain Tumor Detection using Machine Learning and Convolutional Neural Network
Bhuvaneshwari Shetty, Roshan Fernandes, Anisha P Rodrigues, P. Vijaya
Abstract
When abnormal cells develop within the brain, a tumor is created. Depending on the size of the tumor and the section of the brain affected, symptoms from all forms of brain tumors might differ. Where symptoms are present, they may include vomiting, headaches, seizures, eyesight issues, and mental changes. Other signs might include the inability to speak or walk, feelings, or unconsciousness. A combination of surgery, radiation therapy, and chemotherapy may be used as treatment. The proposed work developed a binary classifier to detect MRI based brain tumors. The detection of MRI-based brain tumors will be covered in this research paper utilizing the machine learning model and convolutional neural network. An open dataset was used in this study. The dataset consists of 1500 brain MRI images with tumors and 1500 brain MRI images without tumors. The findings indicate that CNN model obtained better accuracy of 98.21% than the machine learning algorithms.