Semantic Segmentation of Spontaneous Intracerebral Hemorrhage, Intraventricular Hemorrhage, and Associated Edema on CT Images Using Deep Learning-Reference-Cited by-同舟云学术

Semantic Segmentation of Spontaneous Intracerebral Hemorrhage, Intraventricular Hemorrhage, and Associated Edema on CT Images Using Deep Learning

Published:2022-11-01 Issue:6 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Kok Yong En^ORCID,Pszczolkowski Stefan^ORCID,Law Zhe Kang^ORCID,Ali Azlinawati^ORCID,Krishnan Kailash^ORCID,Bath Philip M.^ORCID,Sprigg Nikola^ORCID,Dineen Robert A.^ORCID,French Andrew P.^ORCID

Funder

UK National Institute for Health Research Health Technology Assessment Programme

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.220096

Reference21 articles.

1. Spontaneous Intracerebral Hemorrhage

2. Volume-dependent effect of perihaematomal oedema on outcome for spontaneous intracerebral haemorrhages

3. Intraventricular Hemorrhage Severity as a Predictor of Outcome in Intracerebral Hemorrhage

4. Deep Learning for Automated Measurement of Hemorrhage and Perihematomal Edema in Supratentorial Intracerebral Hemorrhage

5. ICHNet: Intracerebral Hemorrhage (ICH) Segmentation Using Deep Learning

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