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Nils D. Forkert
Researcher at University of Calgary
Publications - 252
Citations - 4266
Nils D. Forkert is an academic researcher from University of Calgary. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 25, co-authored 205 publications receiving 2776 citations. Previous affiliations of Nils D. Forkert include University of Hamburg & Eppendorf (Germany).
Papers
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Journal ArticleDOI
DWI-FLAIR mismatch for the identification of patients with acute ischaemic stroke within 4·5 h of symptom onset (PRE-FLAIR): a multicentre observational study
Götz Thomalla,Bastian Cheng,Martin Ebinger,Qing Hao,Thomas Tourdias,Ona Wu,Jong S. Kim,Lorenz Breuer,Oliver C. Singer,Steven Warach,Soren Christensen,András Treszl,Nils D. Forkert,Ivana Galinovic,Michael Rosenkranz,Tobias Engelhorn,Martin Köhrmann,Matthias Endres,Dong-Wha Kang,Vincent Dousset,A. Gregory Sorensen,David S Liebeskind,Jochen B. Fiebach,Jens Fiehler,Christian Gerloff +24 more
TL;DR: In this article, a mismatch in visibility of acute ischaemic lesion between diffusion-weighted MRI (DWI) and fluid-attenuated inversion recovery (FLAIR) MRI was used to detect patients within the recommended time window for thrombolysis.
Journal ArticleDOI
Influence of Stroke Infarct Location on Functional Outcome Measured by the Modified Rankin Scale
Bastian Cheng,Nils D. Forkert,Melissa Zavaglia,Claus C. Hilgetag,Amir Golsari,Susanne Siemonsen,Jens Fiehler,Salvador Pedraza,Josep Puig,Tae-Hee Cho,Josef A. Alawneh,Jean-Claude Baron,Leif Østergaard,Christian Gerloff,Götz Thomalla +14 more
TL;DR: In the early days after ischemic stroke, information on structural brain damage from MRI supports prognosis of functional outcome as mentioned in this paper, which is rated widely by the modified Rankin Scale that correlates only moderately with lesion volume.
Journal ArticleDOI
Magnetic Particle Imaging for Real-Time Perfusion Imaging in Acute Stroke
Peter Ludewig,Nadine Gdaniec,Jan Sedlacik,Nils D. Forkert,Patryk Szwargulski,Matthias Graeser,Gerhard Adam,Michael G. Kaul,Kannan M. Krishnan,R. Matthew Ferguson,Amit P. Khandhar,Piotr Walczak,Piotr Walczak,Jens Fiehler,Götz Thomalla,Christian Gerloff,Tobias Knopp,Tim Magnus,Tim Magnus +18 more
TL;DR: For the first time, it is shown that MPI could be used as a diagnostic tool for relevant diseases in vivo, such as an ischemic stroke, due to its shorter image acquisition times and increased temporal resolution compared to that of MRI or CT.
Journal ArticleDOI
Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
TL;DR: The results of this study reveal that high-level machine learning methods lead to significantly better segmentation results compared to the rather simple classification methods, pointing towards a difficult non-linear problem.
Journal ArticleDOI
DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes.
Giles Tetteh,Velizar Efremov,Velizar Efremov,Nils D. Forkert,Matthias Schneider,Jan S. Kirschke,Bruno Weber,Claus Zimmer,Marie Piraud,Bjoern H. Menze,Bjoern H. Menze +10 more
TL;DR: The DeepVesselNet architecture does not use any form of sub-sampling layer and works well for vessel segmentation, centerline prediction, and bifurcation detection, and the results show that cross-hair filters achieve over 23% improvement in speed, lower memory footprint, lower network complexity which prevents overfitting and comparable accuracy that does not differ from full 3-D filters.