Changes for page TVB PIPELINE

Last modified by ldomide on 2024/05/20 08:56
From version 24.1
edited by michaels
on 2020/05/07 14:05
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To version 32.1
edited by michaels
on 2020/06/26 12:24
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5 -= From MRI to Functional and Structural Connectivity =
5 += TVB Image Processing Pipeline With MINDS annotated Outputs =
6 6  
7 -Neuroimaging data preprocessing pipeline
8 -
9 9  == [[Pipeline Video Tutorial>>https://drive.google.com/file/d/1VcXf3GX3KoihF4UzJQXzuGL4XWoqj5Jr/view||rel="noopener noreferrer" target="_blank"]] ==
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11 11  == [[Direct link to notebook>>https://drive.ebrains.eu/#my-libs/lib/42ac27a5-981e-4cf6-8ec5-d67b0c24bf09/notebooks||rel="noopener noreferrer" target="_blank"]] ==
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38 38  == What can I find here? ==
39 39  
40 40  * an IPython notebook that describes how to
41 -** use the TVB pipeline on one of the associated supercomputers using PyUnicore
42 -** upload model data to the supercomputer
24 +** use the TVB processing pipeline on one of the associated supercomputers using PyUnicore
25 +** upload MRI data to the supercomputer
43 43  ** set up and run the pipeline
44 44  ** download processing results
45 45  
29 +== What does the TVB processing pipeline do? ==
30 +
31 +After uploading MRI data to the supercomputer, the pipeline runs the three containers
32 +
33 +* [[bids/mrtrix3_connectome>>https://hub.docker.com/r/bids/mrtrix3_connectome||rel="noopener noreferrer" target="_blank"]]
34 +* [[poldracklab/fmriprep>>https://hub.docker.com/r/poldracklab/fmriprep||rel="noopener noreferrer" target="_blank"]], and
35 +* [[thevirtualbrain/tvb_converter>>https://hub.docker.com/r/thevirtualbrain/tvb_converter||rel="noopener noreferrer" target="_blank"]]
36 +
37 +The TVB Processing Pipeline takes multimodal MRI data sets (anatomical, functional and diffusion-weighted MRI) as input and generates SCs, region-average fMRI time series, FCs, brain surfaces, electrode positions, lead field matrices, and atlas parcellations as output. The pipeline performs preprocessing and distortion-correction on MRI data as well as white matter fiber bundle tractography on diffusion data. Outputs are formatted according to two data standards: a TVB-ready data set that can be directly used to simulate brain network models and the same output in BIDS format.
38 +
46 46  == How do I use it? ==
47 47  
48 48  * the pipeline is implemented by three Docker containers (mrtrix3_connectome, fmriprep and tvb_converter)
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99 99  
100 100  * [[https:~~/~~/www.ncbi.nlm.nih.gov/pubmed/25837600>>url:https://www.ncbi.nlm.nih.gov/pubmed/25837600]]
101 101  * [[https:~~/~~/www.ncbi.nlm.nih.gov/pubmed/27480624>>url:https://www.ncbi.nlm.nih.gov/pubmed/27480624]]
95 +
96 +== Citing this work ==
97 +
98 +
99 +When using this pipeline for published work, please acknowledge MRtrix3, MRtrix3_connectome (R. Smith & Connelly, 2019; Tournier et al., 2019) and fmriprep (Esteban et al., 2019).
100 +
101 +
102 +Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S. S., Wright, J., Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. //Nature Methods//. [[https:~~/~~/doi.org/10.1038/s41592-018-0235-4>>https://doi.org/10.1038/s41592-018-0235-4]]
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105 +Schirner, M., Rothmeier, S., Jirsa, V. K., McIntosh, A. R., & Ritter, P. (2015). An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data. NeuroImage, 117, 343-357.  
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108 +Smith, R., & Connelly, A. (2019). MRtrix3_connectome: A BIDS Application for quantitative structural connectome construction. //OHBM//, W610.
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110 +
111 +Tournier, J. D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C. H., & Connelly, A. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. In //NeuroImage//. https:~/~/doi.org/10.1016/j.neuroimage.2019.116137
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Collaboratory.Apps.Collab.Code.CollabClass[0]
Description
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1 -Construct brain network models from empirical MRI data.
1 +TVB Image Processing Pipeline With MINDS annotated Outputs
Public

TVB PIPELINE