Stroke treatment decision support by Artificial Intelligence for analysis of MR images (Stairs)

In stroke, fast diagnosis and treatment is key to prevent oxygen shortage from causing irreversible cell death. CT imaging has been the predominant method of choice for diagnosis. The AMC and Nico.lab have developed Artificial Intelligence (AI) methods for automated CT image analysis tasks to improve the stroke workup in clinical practice. As an alternative to CT, MR imaging gives an unprecedented view on the stroke brain, holding a strong promise for improving diagnosis and treatment selection. The development of AI methods for MR images will enhance the decision making process for stroke patients. We therefore aim to develop stroke treatment decision support by AI for analysis of MR images, in which Amsterdam UMC joins forces with Nico.lab.




FastMRI challenge: winning model in single channel 4x category (paper, code)

Calgary reconstruction challenge: winning deep learning model in both categories (link, code)