This repository is a comprehensive collection of resources that aims to address the critical task of detecting, classifying, and localizing brain tumors in MRI images. The deep learning project utilized state-of-the-art technology to develop a robust and efficient system for diagnosing brain tumors, with the AlexNet CNN model serving as the primary deep learning model. The model is designed to analyze large datasets of MRI images and accurately identify the presence of brain tumors, while also classifying them into different categories based on their characteristics.
The development of this project is a significant breakthrough in the field of medical diagnosis, as it can help physicians to detect and diagnose brain tumors at an early stage, leading to more effective treatments and better patient outcomes. Moreover, the project was published at the prestigious Information Technology and Control publication avenue, indicating its academic and practical significance. The paper has been made available for free at the link provided, enabling researchers and practitioners to access and use the research findings for further advancements in the field of medical diagnosis.
The dataset used in this project can be found at: Link