JIST statistics

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Citations per year

Number of citations per year for the bioinformatics software tool JIST
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Tool usage distribution map

This map represents all the scientific publications referring to JIST per scientific context
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JIST specifications

Information


Unique identifier OMICS_26156
Name JIST
Alternative name Java Image Science Toolkit
Software type Application/Script
Interface Command line interface, Application programming interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
License GNU Lesser General Public License version 3.0
Computer skills Advanced
Version 3.2
Stability Stable
Requirements
MIPAV
Maintained Yes

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Additional information


https://www.nitrc.org/projects/jist/ https://idoimaging.com/programs/32

Publication for Java Image Science Toolkit

JIST citations

 (10)
library_books

Physical Exercise and Spatial Training: A Longitudinal Study of Effects on Cognition, Growth Factors, and Hippocampal Plasticity

2018
Sci Rep
PMCID: 5844866
PMID: 29523857
DOI: 10.1038/s41598-018-19993-9

[…] ntra- and inter-assay coefficients were 4.2% and 6.5% for VEGF, 6.1% and 8.9% for BDNF, and 7.9% and 10.7% for IGF-I.7 T MRI Data: MR Image preprocessing was done using CBSTools and tools from MIPAV, JIST, and ANTs integrated into an automated JIST processing pipeline. First, we obtained brain masks for each subject and time point based on the second inversion and T1 map acquired with MP2RAGE. A d […]

library_books

Quantitative spinal cord MRI in radiologically isolated syndrome

2018
PMCID: 5773843
PMID: 29359174
DOI: 10.1212/NXI.0000000000000436

[…] alculate MTR (figure e-1 at http://links.lww.com/NXI/A25).Each diffusion-weighted image was registered to the initial b0 volume using a 6 degree-of-freedom, rigid-body registration in FLIRT using the Java Image Science Toolkit. The diffusion tensor and maps of DTI indices (fractional anisotropy [FA], mean diffusivity [MD], perpendicular diffusivity [λ⊥], and parallel diffusivity [λ||]), which were […]

library_books

ATPP: A Pipeline for Automatic Tractography Based Brain Parcellation

2017
Front Neuroinform
PMCID: 5447055
PMID: 28611620
DOI: 10.3389/fninf.2017.00035

[…] i et al., ) of parallel workflow tools: (1) flexible workflow tools that allow users to customize automated workflows for any purpose, e.g., Laboratory of Neuro Imaging (LONI) Pipline (Rex et al., ), Java Image Science Toolkit (JIST) (Lucas et al., ), and Nipype (Gorgolewski et al., ); (2) fixed workflow tools that provide a completely established data processing workflow for a particular purpose, […]

library_books

A Systematic Relationship Between Functional Connectivity and Intracortical Myelin in the Human Cerebral Cortex

2017
PMCID: 5390400
PMID: 28184415
DOI: 10.1093/cercor/bhx030

[…] processing and analyses were performed on Linux servers running Ubuntu 12.04.5 LTS. The following software tools were used for data processing: CBS Tools (v3.0, ) as a plugin for MIPAV (v7.0.1, ) and JIST (v2.0, ), ANTs (v2.1.0, ), Nipype (v0.11.0, ), Nilearn (v0.2.3, ), Meshlab (v1.3.0, meshlab.sourceforge.net), Freesurfer (v5.3.0, ; ), and AFNI (v16.1.28, ). Custom scripts were written in Python […]

library_books

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions

2016
PMCID: 4983640
PMID: 27551666
DOI: 10.1016/j.nicl.2016.07.015

[…] ence. All scanning parameters were clinically optimized for each acquired image.For image preprocessing, we used Medical Image Processing Analysis and Visualization (http://mipav.cit.nih.gov) and the Java Image Science Toolkit (http://www.nitrc.org/projects/jist) (). All images for each subject at each visit were interpolated to a voxel size of 1 mm3 and rigidly co-registered longitudinally and ac […]

library_books

Relating multi sequence longitudinal intensity profiles and clinical covariates in incident multiple sclerosis lesions

2015
PMCID: 4660378
PMID: 26693397
DOI: 10.1016/j.nicl.2015.10.013

[…] uence. The scanning parameters were clinically optimized for each acquired image.For image preprocessing, we use Medical Image Processing Analysis and Visualization (http://mipav.cit.nih.gov) and the Java Image Science Toolkit (http://www.nitrc.org/projects/jist) (). We interpolate all images for each subject at each visit to a voxel size of 1 mm3 and rigidly co-register all volumes longitudinally […]


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JIST institution(s)
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA; National Institute on Aging, National Institute of Health, Baltimore, MD, USA; Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
JIST funding source(s)
Supported by NIH/NINDS 5R01NS037747 and 1R01NS056307 and NIH/NIA N01-AG-4-0012.

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