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BEaST specifications

Information


Unique identifier OMICS_25877
Name BEaST
Alternative name Brain Extraction based on nonlocal Segmentation Technique
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C
Computer skills Advanced
Version 0.2
Stability Stable
Source code URL https://codeload.github.com/BIC-MNI/BEaST/zip/release-1.16.00
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Simon Eskildsen

Publication for Brain Extraction based on nonlocal Segmentation Technique

BEaST citations

 (13)
library_books

Amyloid and tau signatures of brain metabolic decline in preclinical Alzheimer’s disease

2018
Eur J Nucl Med Mol Imaging
PMCID: 5915512
PMID: 29396637
DOI: 10.1007/s00259-018-3933-3

[…] MRI and PET acquisitions followed the ADNI protocols (http://adni.loni.usc.edu/methods). The MRI T1-weighted images underwent nonuniformity correction, brain masking and segmentation using the Brain Extraction based on nonlocal Segmentation Technique []. The T1-weighted images were then processed using the CIVET image-processing pipeline and registered using a nine-parameter affine transfor […]

library_books

Playing Super Mario 64 increases hippocampal grey matter in older adults

2017
PLoS One
PMCID: 5718432
PMID: 29211727
DOI: 10.1371/journal.pone.0187779

[…] transformation using ICBM 152 atlases []. The neck was then removed from the scans using a head mask of the brain with open-source MINC tools (http://www.bic.mni.mcgill.ca/ServicesSoftware/MINC). The BEAST algorithm was used to linearly normalize the intensity of scans, masked individually using a brain mask generated in model space []. INSECT (Intensity Normalized Stereotaxic Environment for the […]

library_books

Association of monoamine oxidase A genetic variants and amygdala morphology in violent offenders with antisocial personality disorder and high psychopathic traits

2017
Sci Rep
PMCID: 5575239
PMID: 28851912
DOI: 10.1038/s41598-017-08351-w

[…] uded rigid (6-parameter) registration to MNI space, cropping of the neck region to improve downstream image processing, N4 correction of bias field intensity inhomogeneity, and brain extraction using BeAST. […]

library_books

Early changes in brain structure correlate with language outcomes in children with neonatal encephalopathy

2017
PMCID: 5593272
PMID: 28924555
DOI: 10.1016/j.nicl.2017.06.015

[…] ults of Fonov and colleagues (). We performed additional processing to correct for intensity inhomogeneity due to positioning of subjects' heads within the coil.We obtained accurate brain masks using BEaST, a nonlocal mean-based label-fusion algorithm () which was trained with 20 individual images (selected randomly from the set of 6 month images) with manually-labeled brain masks. The final templ […]

library_books

Family history and APOE4 risk for Alzheimer's disease impact the neural correlates of episodic memory by early midlife

2017
PMCID: 5385589
PMID: 28413778
DOI: 10.1016/j.nicl.2017.03.016

[…] by their intracranial volume (ICV) to control for head size by dividing hippocampal volume/ICV. ICV for each subject was obtained using the brain extraction based on nonlocal segmentation technique [BEaST] (). Manual quality assurance was performed on ICV labels. A one-way between group ANOVA was conducted to compare right hippocampal volume (corrected by ICV) across groups, with Tukey's post-hoc […]

call_split

Detection of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Longitudinal Brain MRI

2017
Front Neuroinform
PMCID: 5323395
PMID: 28286479
DOI: 10.3389/fninf.2017.00016
call_split See protocol

[…] tion. All images were preprocessed through the same fully automatic pipeline, as described by Coupé et al. (). Inside this pipeline, the inhomogeneities are corrected by N3, the brain is extracted by BEaST (Eskildsen et al., ), and the intensity is linearly normalized to the MNI template intensity. After preprocessing each image independently using these identical steps, all follow-up images are r […]

Citations

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BEaST institution(s)
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Department of Health Science and Technology, Aalborg University, Aalborg, Denmark; Instituto de Aplicaciones de las Tecnologias de la Informacion y de las Comunicaciones Avanzadas (ITACA), Universidad Politecnica de Valencia, Valencia, Spain; Dementia Research Centre (DRC), UCL Institute of Neurology, London, UK
BEaST funding source(s)
Supported by the Canadian Institutes of Health Research MOP-84360 & MOP-111169 as well as CDA (CECR)-Gevas-OE016, the MRC, ARUK and the NIHR; by the Spanish Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001.

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