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  New tissue priors for improved automated classification of subcortical brain structures on MRI

Lorio, S., Fresard, S., Adaszewski, S., Kherif, F., Chowdhury, R., Frackowiak, R. S., et al. (2016). New tissue priors for improved automated classification of subcortical brain structures on MRI. NeuroImage, 130, 157-166. doi:10.1016/j.neuroimage.2016.01.062.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0029-AC85-9 Version Permalink: https://hdl.handle.net/21.11116/0000-0003-AB9B-E
Genre: Journal Article

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 Creators:
Lorio, S.1, Author
Fresard, S.1, Author
Adaszewski, S.1, Author
Kherif, F.1, Author
Chowdhury, R.2, Author
Frackowiak, Richard S.1, Author
Ashburner, John2, Author
Helms, Gunther3, Author
Weiskopf, Nikolaus2, 4, Author           
Lutti, Antoine1, Author
Draganski, Bogdan1, 5, Author           
Affiliations:
1Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
2Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
3Department of Medical Radiation Physics, Skånes University Hospital, Lund, Sweden, ou_persistent22              
4Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
5Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_634549              

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Free keywords: Relaxometry; Basal ganglia; Effective transverse relaxation; Magnetization transfer saturation; Tissue probability maps; Voxel-based morphometry; Voxel-based quantification
 Abstract: Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low grey-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related grey-white matter contrast changes. Aiming to improve the anatomical plausibility of automated brain tissue classification from T1w data, we have created new tissue probability maps for subcortical grey matter regions. Supported by atlas-derived spatial information, raters manually labelled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal grey-white matter contrast in these areas. After assessment of inter-rater variability, the new tissue priors were tested on T1w data within the framework of voxel-based morphometry. The automated detection of grey matter in subcortical areas with our new probability maps was more anatomically plausible compared to the one derived with currently available priors. We provide evidence that the improved delineation compensates age-related bias in the segmentation of iron rich subcortical regions. The new tissue priors, allowing robust detection of basal ganglia and thalamus, have the potential to enhance the sensitivity of voxel-based morphometry in both healthy and diseased brains.

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Language(s): eng - English
 Dates: 2015-10-282016-01-292016-02-052016-04-15
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2016.01.062
PMID: 26854557
PMC: PMC4819722
Other: Epub 2016
 Degree: -

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Project name : Non-invasive in vivo histology in health and disease using Magnetic Resonance Imaging (MRI) / HMRI
Grant ID : 616905
Funding program : FP7 (ERC-2013-CoG)
Funding organization : European Commission (EC)
Project name : Talking imaging into the therapeutic domain: Self-regulation of brain systems for mental disorders / BrainTrain
Grant ID : 602186
Funding program : Funding Programme 7 (FP7-HEALTH-2013-INNOVATION-1)
Funding organization : European Commission (EC)
Project name : -
Grant ID : 320030_135679
Funding program : -
Funding organization : Swiss National Science Foundation (NCCR Synapsy)
Project name : -
Grant ID : SPUM 33CM30_140332/1
Funding program : -
Funding organization : Swiss National Science Foundation (NCCR Synapsy)
Project name : -
Grant ID : -
Funding program : -
Funding organization : Foundation Parkinson Switzerland
Project name : -
Grant ID : -
Funding program : -
Funding organization : Foundation Synapsis
Project name : -
Grant ID : -
Funding program : -
Funding organization : Roger de Spoelberch Foundation
Project name : -
Grant ID : -
Funding program : -
Funding organization : Partridge Foundation
Project name : -
Grant ID : 0915/Z/10/Z
Funding program : -
Funding organization : Wellcome Trust
Project name : The Human Brain Project / HBP
Grant ID : 604102
Funding program : Funding Programme 7 (FP7)
Funding organization : European Commission (EC)

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 130 Sequence Number: - Start / End Page: 157 - 166 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166