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MAGeT specifications

Information


Unique identifier OMICS_29878
Name MAGeT
Alternative names Multiple Automatically Generated Templates brain segmentation algorithm, MAGeTbrain
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Perl, Python, Shell (Bash)
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes

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Documentation


Publications for Multiple Automatically Generated Templates brain segmentation algorithm

MAGeT citations

 (42)
library_books

Longitudinal development of hippocampal subregions from childhood to adulthood

2018
PMCID: 5945606
PMID: 29597156
DOI: 10.1016/j.dcn.2018.03.009

[…] eSurfer automated method used in the present study and other available automated methods such as Automatic Segmentation of Hippocampal Subfields (ASHS) (), Multiple Automatically Generated Templates (MAGeT) () and Advanced Neuroimaging Tools (ANTs) (), are also lacking (see () for such a study, comparing ASHS, ANTs and manual segmentation in child, adolescent, and adult age groups), but critical i […]

library_books

Versatile Antagonistic Activities of Soil Borne Bacillus spp. and Pseudomonas spp. against Phytophthora infestans and Other Potato Pathogens

2018
Front Microbiol
PMCID: 5816801
PMID: 29487574
DOI: 10.3389/fmicb.2018.00143

[…] it direct antifungal and anti-oomycetal activity (Yu et al., ; Ongena et al., ; Raaijmakers et al., ). Their fungi-toxicity is mediated by mechanisms involving pore formation in the plasmic membrane (Maget-Dana et al., ; Ongena and Jacques, ). Similarly, cyclic lipopeptides (cLPS) produced by Pseudomonas spp. have direct antifungal and anti-oomycetal activities (Yang et al., ). Cyclic lipopeptides […]

call_split

Healthy versus Entorhinal Cortical Atrophy Identification in Asymptomatic APOE4 Carriers at Risk for Alzheimer’s Disease

2018
PMCID: 5798531
PMID: 29278888
DOI: 10.3233/JAD-170540
call_split See protocol

[…] allele carriers: n = 13, t = 10.02; non-ɛ4 carriers: n = 47, t = 5.43).Fully-automated segmentation of the hippocampus subfields was carried out using the Multiple Automatically Generated Templates (MAGeT) Brain algorithm []. This technique is a modified multi-atlas segmentation technique designed to use a limited number of high-quality manually segmented atlases as input. Participant scans were […]

library_books

Neuroanatomical and Symptomatic Sex Differences in Individuals at Clinical High Risk for Psychosis

2017
PMCID: 5744013
PMID: 29312018
DOI: 10.3389/fpsyt.2017.00291

[…] Bilateral hippocampus and amygdala volumes were extracted from T1 images using the automatic multi-atlas segmentation algorithm, MAGeT Brain (, ). To generate hippocampus and amygdala volumes, we used five high-resolution atlases onto which the structures had been expertly segmented (). These 5 atlases were used to label a set […]

library_books

XKR4 Gene Effects on Cerebellar Development Are Not Specific to ADHD

2017
PMCID: 5732973
PMID: 29311829
DOI: 10.3389/fncel.2017.00396

[…] onal slices (Philips Achieva; 172 scans) with echo time (TE) 4.6 ms; repetition time (TR) 30 ms; flip angle 30°; field of view (FOV) 256 mm; in-plane voxel size 1 mm × 1 mm.Scans were processed using MAGeT-Brain, an automated multi-atlas segmentation pipeline for anatomical MRI. Technical details of the segmentation can be found elsewhere (). Briefly, MAGeT-Brain uses multiple manually labeled hig […]

library_books

Anticancer Activities of Surfactin and Potential Application of Nanotechnology Assisted Surfactin Delivery

2017
Front Pharmacol
PMCID: 5662584
PMID: 29123482
DOI: 10.3389/fphar.2017.00761

[…] nteraction with dimyristoylphosphatidylcholine (DMPC) compared to L-α-dimyristoylphosphatidylethanolamine (DMPE) and L-α-dimyristoylphosphatidic acid (DMPA) monolayers due to electrostatic repulsion (Maget-Dana and Ptak, ). Surfactin penetration across the lipids is greater when the acyl chain length of the phospholipids decreases (Maget-Dana and Ptak, ; Liu X. et al., ). Furthermore, the miscibil […]

Citations

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MAGeT institution(s)
Kimel Family Translational Imaging-Genetics Lab, Centre for Addiction and Mental Health, Toronto, ON, Canada; Neurosciences and Mental Health Laboratory, Hospital for Sick Children, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Douglas Mental Health University Institute, Verdun, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Rotman Research Institute, Baycrest, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
MAGeT funding source(s)
Supported by NIH grants P30 AG010129 and K01 AG030514.

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