Prediction of tissue outcome in acute ischemic stroke based on single-phase CT angiography at admission

IntroductionIn acute ischemic stroke, prediction of the tissue outcome after reperfusion can be used to identify patients that might benefit from mechanical thrombectomy (MT). The aim of this work was to develop a deep learning model that can predict the follow-up infarct location and extent exclusi...

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Автори:	Frosti Palsson, Nils D. Forkert, Lukas Meyer, Gabriel Broocks, Fabian Flottmann, Máté E. Maros, Matthias Bechstein, Laurens Winkelmeier, Eckhard Schlemm, Jens Fiehler, Susanne Gellißen, Helge C. Kniep
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Frontiers Media S.A. 2024-03-01
Серія:	Frontiers in Neurology
Предмети:	stroke infarct core mechanical thrombectomy deep learning segmentation
Онлайн доступ:	https://www.frontiersin.org/articles/10.3389/fneur.2024.1330497/full
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