Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury

Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury

IntroductionRadiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentat...

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Bibliographic Details
Main Authors: Bradley J. MacIntosh, Qinghui Liu, Till Schellhorn, Mona K. Beyer, Inge Rasmus Groote, Pål C. Morberg, Joshua M. Poulin, Maiken N. Selseth, Ragnhild C. Bakke, Aina Naqvi, Amir Hillal, Teresa Ullberg, Johan Wassélius, Ole M. Rønning, Per Selnes, Espen S. Kristoffersen, Kyrre Eeg Emblem, Karoline Skogen, Else C. Sandset, Atle Bjørnerud
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Neurology
Subjects:
computed tomography
intracerebral hemorrhage
stroke
traumatic brain injury
segmentation
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2023.1244672/full

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https://www.frontiersin.org/articles/10.3389/fneur.2023.1244672/full

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