Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study-Reference-Cited by-同舟云学术

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

Published:2020-06 Issue:6 Volume:2 Page:e314-e322
ISSN:2589-7500
Container-title:The Lancet Digital Health
language:en
Short-container-title:The Lancet Digital Health

Author:

Monteiro Miguel,Newcombe Virginia F J,Mathieu Francois,Adatia Krishma,Kamnitsas Konstantinos,Ferrante Enzo,Das Tilak,Whitehouse Daniel,Rueckert Daniel,Menon David K,Glocker Ben

Funder

European Union 7th Framework Programme

European Research Council Horizon 2020

Publisher

Elsevier BV

Subject

Health Information Management,Decision Sciences (miscellaneous),Health Informatics,Medicine (miscellaneous)

Reference30 articles.

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4. Guidelines for the management of severe traumatic brain injury, fourth edition;Carney;Neurosurgery,2017

5. Central versus local radiological reading of acute computed tomography characteristics in multi-center traumatic brain injury research;Vande Vyvere;J Neurotrauma,2019

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