Deep Convolutional Neural Network Model to Enhance Brain Tumor Segmentation on Magnetic Resonance Brain Images

The detection of brain tumors using MRI images is an important undertaking within medical imaging with hopes of early intervention and accurate classification. This work investigates meningioma tumors identifying from MRI scans employing a convolutional neural network (CNN). Techniques for data augmentation improve the dataset to enhance model generalization. The model under consideration classifies MRI images of the head, segments the areas with the tumor applying contouring and thresholding techniques, and marks them. The study states results, discusses, and suggests ways to improve the analysis of medical images in the future. The work aims at the development of automated systems for medical diagnostics with minimum human intervention to increase efficiency and precision in diagnoses. Key Words: Deep Learning, Classification, Medical Imaging, Image Processing, Data Augmentation, MRI, Brain tumor detection, Convolutional Neural Network.