2023
Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model
ZHU, K.; F. BALA; J. ZHANG; F. BENALI; Petra CIMFLOVÁ et. al.Basic information
Original name
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.; F. BALA; J. ZHANG; F. BENALI; Petra CIMFLOVÁ (203 Czech Republic, belonging to the institution); B. J. KIM; R. MCDONOUGH; N. SINGH; M. D. HILL; M. GOYAL; A. DEMCHUK; B. K. MENON and W. QIU (guarantor)
Edition
American Journal of Neuroradiology, Denville, American Society of Neuroradiology, 2023, 0195-6108
Other information
Language
English
Type of outcome
Article in a journal
Field of Study
30224 Radiology, nuclear medicine and medical imaging
Country of publisher
United States of America
Confidentiality degree
is not subject to a state or trade secret
References:
Impact factor
Impact factor: 3.100
RIV identification code
RIV/00216224:14110/23:00133284
Organization unit
Faculty of Medicine
UT WoS
000992249000001
EID Scopus
2-s2.0-85163907252
Keywords in English
Intracranial Thrombus; Automated Segmentation; NCCT; CTA; Acute Ischemic Strok
Tags
Tags
International impact, Reviewed
Changed: 29/1/2024 12:10, Mgr. Tereza Miškechová
Abstract
V originále
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.