CODAvision: best practices and a user-friendly interface for rapid, customizable segmentation of medical images
Valentina Matos-Romero, Jaime Gómez-Becerril, André Forjaz, Lucie Dequiedt, Tyler Newton, Saurabh Joshi, Yu Shen, Eban A. Hanna, Praful R. Nair, Arrun Sivasubramanian, Si-Han Wang, Emily L. Lasse Opsahl, Alexander T.F. Bell, Diogo Fróis-Vieira, Julianna M. Czum, , Ashley L. Kiemen
CODAvision provides a user-friendly interface for rapid, customizable medical image segmentation using deep learning, enabling non-experts to train and evaluate models across diverse imaging modalities.
Nature Protocols · Jul 7, 2026Peer-reviewedBioinformatics