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Fully Automated Thrombus Segmentation on CT Images of Patients with Acute Ischemic Stroke

Thrombus imaging characteristics are associated with treatment success and functional outcomes in stroke patients. However, assessing these characteristics based on manual annotations is labor intensive and subject to observer bias. Therefore, we aimed to create an automated pipeline for consistent...

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Автори: Mahsa Mojtahedi, Manon Kappelhof, Elena Ponomareva, Manon Tolhuisen, Ivo Jansen, Agnetha A. E. Bruggeman, Bruna G. Dutra, Lonneke Yo, Natalie LeCouffe, Jan W. Hoving, Henk van Voorst, Josje Brouwer, Nerea Arrarte Terreros, Praneeta Konduri, Frederick J. A. Meijer, Auke Appelman, Kilian M. Treurniet, Jonathan M. Coutinho, Yvo Roos, Wim van Zwam, Diederik Dippel, Efstratios Gavves, Bart J. Emmer, Charles Majoie, Henk Marquering
Формат: Artigo
Мова:Inglês
Опубліковано: MDPI AG 2022-03-01
Серія:Diagnostics
Предмети:
ischemic stroke
thrombus
segmentation
CT imaging
CT angiography
convolutional neural network (CNN)
Онлайн доступ:https://www.mdpi.com/2075-4418/12/3/698
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