ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI-Reference-Cited by-同舟云学术

ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI

Published:2018-09-13 Issue: Volume:9 Page:
ISSN:1664-2295
Container-title:Frontiers in Neurology
language:
Short-container-title:Front. Neurol.

Author:

Winzeck Stefan,Hakim Arsany,McKinley Richard,Pinto José A. A. D. S. R.,Alves Victor,Silva Carlos,Pisov Maxim,Krivov Egor,Belyaev Mikhail,Monteiro Miguel,Oliveira Arlindo,Choi Youngwon,Paik Myunghee Cho,Kwon Yongchan,Lee Hanbyul,Kim Beom Joon,Won Joong-Ho,Islam Mobarakol,Ren Hongliang,Robben David,Suetens Paul,Gong Enhao,Niu Yilin,Xu Junshen,Pauly John M.,Lucas Christian,Heinrich Mattias P.,Rivera Luis C.,Castillo Laura S.,Daza Laura A.,Beers Andrew L.,Arbelaezs Pablo,Maier Oskar,Chang Ken,Brown James M.,Kalpathy-Cramer Jayashree,Zaharchuk Greg,Wiest Roland,Reyes Mauricio

Publisher

Frontiers Media SA

Subject

Clinical Neurology,Neurology

Reference41 articles.

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3. Fully automated stroke tissue estimation using random forest classifiers (FASTER);McKinley;J Cereb Blood Flow Metab,2017

4. Automated segmentation of chronic stroke lesions using LINDA: lesion identification with neighborhood data analysis;Pustina;Human Brain Mapp,2016

5. White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks;Guerrero;NeuroImage Clin,2018

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