Employing CNN Features for Automated Brain Tumor Classification in MRI - Parkhi, Priya; Hambarde, Bhagyashree; Agrawal, Poorva; Vishwakarma, Muktinath (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Brain tumor is a rapid growth of nerves cell ultimately it form a mass of cell. Tumour found in any part of brain. Finding the proper position of tumor is sometime very difficult task. This problem is solving by deep learning techniques. Deep learning is a neural architecture and learns from data. It is a mostly cause of death all around the world. So proper solution to this problem is required. This research focused on diagnoses tumours in early stage, using an innovative approach to improve the accuracy and efficiency of brain tumor detection using Convolutional Neural Networks (CNNs). This model objective is to identifying abnormal images and segmenting the tumor region using multi-level thresholding. This segmentation aids in estimating tumor density for treatment planning. By leveraging deep learning and advanced image analysis, it aims to create a reliable and automated system for brain tumor detection.