A Multi-Class Brain Tumor Classifier using Convolutional Neural Network with 99% Accuracy achieved by applying the method of Transfer Learning using Python and Pytorch Deep Learning Framework

Brainy is a virtual MRI analyzer. Just upload the MRI scan file and get 3 different classes of tumors detected and segmented. In Beta.

Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.

A Flask-based web app for brain tumour classification from MRI scans using pre-trained deep learning models. Supports Glioma, Meningioma, Pituitary, and No Tumor detection with model selection and confidence scoring.

SOTA 3D Medical Segmentation framework (UNET++, TransUNET , SwimTransUNET) in TensorFlow. Fully TPU-optimized with a 3-stage OHEM pipeline for the Medical Segmentation Decathlon (MSD).

Image classification of brain tumours using convolutional neural networks.

Brain MRI tumour detection, classification, segmentation and GAN synthesis — Docker + Kubernetes + Ansible deployment stack.

A multi-organ tumour detection using deep learning. Distinction graded Post Graduate Project achieving 93.15% Dice score

NeuroCare_AI is an AI-powered neurology and brain health research platform. Content is compiled from published medical literature, clinical guidelines (AAN, AHA/ASA, WHO), and research databases. It enables upload and analysis of reports. This open, collaborative system grows stronger with every user. Share it widely.