Russia

Russian Federation

Pakistan

Islamic Republic of Pakistan

<p>This project presents an optimized VGG16-based deep learning system for automated brain tumor classification from MRI scans, achieving 94% accuracy and a mean AUC of 0.991 across four classes — Glioma, Meningioma, Pituitary, and No Tumor — using a dataset of 7,023 images. The model incorporates Grad-CAM explainability for clinical transparency, showing radiologists exactly which brain region influenced each decision. A comparative study of five CNN architectures under identical conditions confirmed VGG16 as the best performer, and the complete system was deployed as a clinical web application with tumor segmentation, brain region mapping, and uncertainty detection.</p>


C008B9-doctors

Optimized VGG16-Based Deep Learning Model for Multi-Class Brain Tumor Classification from MRI Images

<p>I am Nadeem Rehmat, a biotechnologist and researcher from Pakistan currently studying at Saint Petersburg Electrotechnical University "LETI" in Russia. With a background in laboratory science and deep learning, I recently developed an AI-powered brain tumor MRI classification system achieving 94% accuracy, combining my passion for technology with real-world healthcare impact.</p>


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