Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations

Cerebrovascular diseases, in particular ischemic stroke, are one of the leading global causes of death in developed countries. Perfusion CT and/or MRI are ideal imaging modalities for characterizing affected ischemic tissue in the hyper-acute phase. If infarct growth over time could be predicted acc...

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Detalles Bibliográficos
Autores principales: Lucas, Christian, Kemmling, André, Bouteldja, Nassim, Aulmann, Linda F., Madany Mamlouk, Amir, Heinrich, Mattias P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275324/
https://www.ncbi.nlm.nih.gov/pubmed/30534108
http://dx.doi.org/10.3389/fneur.2018.00989

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275324/
https://www.ncbi.nlm.nih.gov/pubmed/30534108
http://dx.doi.org/10.3389/fneur.2018.00989

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