Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations.

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Title: Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations.
Authors: Azor AM; Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom.; Dyson School of Design Engineering, Imperial College London, South Kensington Campus, London, United Kingdom.; The Royal British Legion, Centre for Blast Injury Studies, Imperial College London, South Kensington Campus, London, United Kingdom., Sharp DJ; Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom.; Dyson School of Design Engineering, Imperial College London, South Kensington Campus, London, United Kingdom.; Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, United Kingdom., Jolly AE; Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom.; Care Research & Technology Centre, UK Dementia Research Institute, Imperial College London, London, United Kingdom., Bourke NJ; Computational, Cognitive and Clinical Neuroimaging Laboratory, Hammersmith Hospital, London, United Kingdom., Hellyer PJ; Centre for Neuroimaging Sciences, King's College London, London, United Kingdom.
Source: PloS one [PLoS One] 2022 Dec 08; Vol. 17 (12), pp. e0268233. Date of Electronic Publication: 2022 Dec 08 (Print Publication: 2022).
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1932-6203
DOI:10.1371/journal.pone.0268233