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MRICloud specifications


Unique identifier OMICS_30939
Name MRICloud
Software type Application/Script
Interface Graphical user interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux
Computer skills Medium
Stability Stable
High performance computing Yes
Registration required Yes
Maintained Yes


No version available


  • person_outline Susumu Mori

Publication for MRICloud

MRICloud citations


Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?

Front Neuroinform
PMCID: 5675877
PMID: 29163119
DOI: 10.3389/fninf.2017.00063

[…] able Pipeline for the Analysis of Connectomes) is an environment to automate preprocessing and analysis of resting-state fMRI data, and is available as a machine image on EC2 (). Newer platforms like MRICloud shift neuroimaging processing entirely to the cloud, and links different types of service tools to offer an integrated software-as-a-service model that enables users to run analyses and quali […]


Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PMCID: 4896536
PMID: 27279746
DOI: 10.4137/MRI.S23558

[…] mage processing pipelines, brain atlases and/or data sets, and also integrates the underlying platforms and infrastructure—for cloud-based neuroimaging analyses. Two recent examples of BiAaaS include MRICloud and NITRC-CE, which will be discussed in greater detail below.Infrastructure as a Service (IaaS) is the most basic service model (ie, the lowest level of cloud computing; ), where the cloud s […]


Imaging network level language recovery after left PCA stroke

PMCID: 5003759
PMID: 27176918
DOI: 10.3233/RNN-150621

[…] f language tasks (e.g., ; ; ; ). The anatomical mask for each ROI was generated from multiple atlases (45 adult brain atlases, segmented on 289 parcels) and is available at BrainGPS ( Each participant’s high resolution MPRAGE was segmentted by using the multi-atlas mapping and parcellation approach based on the large deformation diffeomorphic metric mapping, LDDMM (; […]


Evaluation of Cross Protocol Stability of a Fully Automated Brain Multi Atlas Parcellation Tool

PLoS One
PMCID: 4514626
PMID: 26208327
DOI: 10.1371/journal.pone.0133533

[…] nt manufacturers and two different field strengths. We also used ADNI AD data for pathology effect analysis. All analyses were performed based on our fully automated T1-image analysis pipeline in the MriCloud platform ( Based on this analysis, we measured the impact of protocol differences on the parcellation results, and compared its extent with two types of biological effect si […]


Segmentation of brain magnetic resonance images based on multi atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles

Front Neurosci
PMCID: 4347448
PMID: 25784852
DOI: 10.3389/fnins.2015.00061

[…] ifying skull-stripping and structure extraction from T1-weighted images of the human brain in a Bayesian parameter estimation setting. This fully automated hierarchical pipeline is implemented in the MriCloud platform ( The pipeline is built on a segmentation label estimation algorithm called multi-atlas likelihood fusion (MALF) (Tang et al., ). MALF relies on the information of […]


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MRICloud institution(s)
Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins University, Whiting School of Engineering, Baltimore, MD, USA; AnatomyWorks, Baltimore, MD, USA
MRICloud funding source(s)
Supported by grants P41EB015909, R01EB017638, and R01NS084957.

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