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@article{190973,
        author = {Prasad Bharat Gaikwad and Siddhesh Ghode and Harsha Dhumal and Gauri Kotekar},
        title = {Automated Brain Tumor Detection from MRI Scans using Deep Learning with Django Web Deployment},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {4541-4546},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190973},
        abstract = {Brain tumor detection is a critical task in medical imaging. Manual diagnosis using MRI scans is time-consuming and error-prone. This paper presents an automated deep learning-based system for detecting and classifying brain tumors using Convolutional Neural Networks (CNNs). Transfer learning models such as VGG16, Efficient Net and ResNet50 are applied to improve classification accuracy on limited datasets. The system is deployed as a web application using Django framework, enabling users to upload MRI scans, obtain classification results, and generate diagnostic reports. Experimental results demonstrate that the system achieves reliable accuracy, assisting radiologists in early detection and treatment planning.},
        keywords = {Brain Tumor, Deep Learning, CNN, ResNet50, Efficient Net, Django, MRI Classification},
        month = {January},
        }