ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI

• Main Authors: Winzeck, S., Hakim, A., McKinley, R., Pinto, J.A.A.D.S.R., Alves, V., Silva, C., Pisov, M., Krivov, E., Belyaev, M., Monteiro, M., Oliveira, A., Choi, Y., Paik, M.C., Kwon, Y., Lee, H., Kim, B.J., Won, J.-H., Islam, M., Ren, H., Robben, D., Suetens, P., Gong, E., Niu, Y., Xu, J., Pauly, J.M., Lucas, C., Heinrich, M.P., Rivera, L.C., Castillo, L.S., Daza, L.A., Beers, A.L., Arbelaezs, P., Maier, O., Chang, K., Brown, J.M., Kalpathy-Cramer, J., Zaharchuk, G., Wiest, R., Reyes, M.
• Other Authors: BIOMEDICAL ENGINEERING
• Format: Article
• Published: Frontiers Media S.A. 2021
• Subjects: Benchmarking; Datasets; Deep learning; Machine learning; MRI; Prediction models; Stroke; Stroke outcome
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/210864
• Institution: National University of Singapore

10.3389/fneur.2018.00679