A reproducible 3D convolutional neural network with dual attention module (3D-DAM) for Alzheimer's disease classification

Alzheimer disease classification using ResNet50

Alzheimer's disease classification from MRI scans using hybrid learning and XAI

This repository contains a comprehensive deep learning solution for Alzheimer's Disease Classification using state-of-the-art DenseNet architectures optimized with Optuna hyperparameter tuning. The project implements multiple DenseNet variants for classification of Alzheimer's disease stages from brain MRI images.

Classifies MRI scans into Non-Demented, Very Mild, Mild, and Moderate Dementia using a fine-tuned VGG16 model. Implements data augmentation, class weighting, and Grad-CAM for interpretability.