| The Cancer Imaging Archive (TCIA) |
https://www.cancerimagingarchive.net/ |
CR, CT, DX, Histopathology, MG, MR, NM, PET, REG, RTSTRUCT, SEG, SR, US, |
The Cancer Imaging Archive (TCIA) is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. |
| Grand Challenge |
https://grand-challenge.org/challenges/ |
CT, Dermoscopy, Endoscopy, Fundus Photograph, Histology, IR, MG, MR, OCT, PET, US, XR |
A platform for end-to-end development of machine learning solutions in biomedical imaging. |
| RAD IMAGE NET |
https://www.radimagenet.com/ |
CT, MR, US, XR |
RadImageNet is a large database of annotated medical images from multiple modalities and of multiple pathologies. The data can be licensed for commercial use. |
| Mathematical Oncology Laboratory (MOLAB) |
https://molab.es/datasets-brain-metastasis-1/?type=metasrd |
MR, NIfTI segmentation, radiomic features |
A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data |
| EUCAIM |
https://dashboard.eucaim.cancerimage.eu/ |
CR, CT, DX, PET, MG, MR, NM, SEG, US |
Cancer Image Europe provides a robust, trustworthy platform for researchers, clinicians, and innovators to access diverse cancer images enabling the benchmarking, testing, and piloting of AI-driven technologies. |