Annotation-free prediction of treatment-specific tissue outcome from 4D CT perfusion imaging in acute ischemic stroke
Author:
Funder
Canada Research Chairs Program
Natural Sciences and Engineering Research Council of Canada
Calgary Foundation
Publisher
Elsevier BV
Reference34 articles.
1. Predicting treatment-specific lesion outcomes in acute ischemic stroke from 4D CT perfusion imaging using spatio-temporal convolutional neural networks;Amador;Med. Image Anal.,2022
2. Amador, K., Winder, A., Fiehler, J., Wilms, M., Forkert, N.D., 2022b. Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging, in: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, Lecture Notes in Computer Science. Springer Nature Switzerland, Cham, pp. 644–654. https://doi.org/10.1007/978-3-031-16437-8_62.
3. Thresholds in cerebral ischemia - the ischemic penumbra;Astrup;Stroke,1981
4. A reproducible evaluation of ANTs similarity metric performance in brain image registration;Avants;NeuroImage,2011
5. Imaging in Acute Stroke;Birenbaum;West J. Emerg. Med.,2011
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