medical-imaging-datasets

Clinically-Interpretable Radiomics [MICCAI'22, CMPB'21]

Open-source 2D/3D registration datasets and dataloaders for DiffDRR

Python package for programmatic access to the National Biomedical Imaging Archive (NBIA) and The Cancer Imaging Archive (TCIA)

NanoNet: Real-Time Polyp Segmentation in Capsule Endoscopy & Colonoscopy [Contains an open-access capsule endoscopy dataset (2021 IEEE CBMS)]

Zero-shot lesion detection pipeline using SAM for dataset generation and YOLOv11 training.

A list of public datasets for medical image analysis

Cross-platform SAM-assisted image annotation and resumable expert review with polygon editing, audit trails, change detection, timing, provenance, and CSV export.

Comprehensive framework for curating and validating biomedical datasets for clinical AI applications

A Dual-Stream Multimodal Fusion Framework for Breast Cancer Detection

ImFlow: A better image dataset loader for TensorFlow

Two-stage chest X-ray classifier: NORMAL vs PNEUMONIA → BACTERIA vs VIRUS. Grad-CAM + Streamlit demo. Educational—not for clinical use.

A PyTorch implementation of Gated Dual-Stream Multiple Instance Learning (DSMIL) for BRCA1/BRCA2 gene expression classification from Whole Slide Images using UNI and CONCH foundation models. Built on TCGA-BRCA with patient-grouped cross-validation

Readers for medical imaging datasets

Exploratory analysis and visualization of a breast cancer histopathology image dataset, including binary and multiclass classification structures across multiple magnification levels.

This project leverages U-Net for lung region segmentation and CNN for cancer classification using CT scan images. It aims to enhance lung cancer detection accuracy through deep learning techniques. The model achieved 97% accuracy and has been validated with a comprehensive dataset.