Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model

• Authors: ZHU K.; BALA F.; ZHANG J.; BENALI F.; CIMFLOVÁ Petra; KIM B. J.; MCDONOUGH R.; SINGH N.; HILL M. D.; GOYAL M.; DEMCHUK A.; MENON B. K.; QIU W.
• Year of publication: 2023
• Type: Article in Periodical
• Magazine / Source: American Journal of Neuroradiology
• MU Faculty or unit: Faculty of Medicine
• Web: https://www.ajnr.org/content/44/6/641
• Doi: http://dx.doi.org/10.3174/ajnr.A7878
• Keywords: Intracranial Thrombus; Automated Segmentation; NCCT; CTA; Acute Ischemic Strok
• Description: BACKGROUND AND PURPOSE: Identifying the presence and extent of intracranial thrombi is crucial in selecting patients with acute ischemic stroke for treatment. This article aims to develop an automated approach to quantify thrombus on NCCT and CTA in patients with stroke.