Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI-Reference-Cited by-同舟云学术

Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI

Published:2019-05-30 Issue:6 Volume:40 Page:938-945
ISSN:0195-6108
Container-title:American Journal of Neuroradiology
language:en
Short-container-title:AJNR Am J Neuroradiol

Author:

Winzeck S.^ORCID,Mocking S.J.T.^ORCID,Bezerra R.^ORCID,Bouts M.J.R.J.^ORCID,McIntosh E.C.^ORCID,Diwan I.^ORCID,Garg P.^ORCID,Chutinet A.^ORCID,Kimberly W.T.^ORCID,Copen W.A.^ORCID,Schaefer P.W.^ORCID,Ay H.^ORCID,Singhal A.B.^ORCID,Kamnitsas K.^ORCID,Glocker B.^ORCID,Sorensen A.G.^ORCID,Wu O.^ORCID

Funder

National Institute of Neurological Disorders and Stroke

National Institutes of Health

National Institute of Biomedical Imaging and Bioengineering

Nvidia

Publisher

American Society of Neuroradiology (ASNR)

Subject

Neurology (clinical),Radiology, Nuclear Medicine and imaging

Reference24 articles.

1. Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks

2. Real-time diffusion-perfusion mismatch analysis in acute stroke