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Multidimensional Neuroimaging Processing in ReCaS Datacenter

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Internet and Distributed Computing Systems (IDCS 2019)

Abstract

In the last decade, a large amount of neuroimaging datasets became publicly available on different archives, so there is an increasing need to manage heterogeneous data, aggregate and process them by means of large-scale computational resources. ReCaS datacenter offers the most important features to manage big datasets, process them, store results in efficient manner and make all the pipeline steps available for reproducible data analysis. Here, we present a scientific computing environment in ReCaS datacenter to deal with common problems of large-scale neuroimaging processing. We show the general architecture of the datacenter and the main steps to perform multidimensional neuroimaging processing.

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Notes

  1. 1.

    http://www.pon-recas.it.

  2. 2.

    http://www.ponsmartcities-prisma.it.

  3. 3.

    https://research.cs.wisc.edu/htcondor/.

References

  1. Amoroso, N., et al.: Medical physics applications in Bari ReCaS farm. In: High Performance Scientific Computing Using Distributed Infrastructures: Results and Scientific Applications Derived from the Italian PON ReCaS Project, pp. 271–278. World Scientific (2017)

    Google Scholar 

  2. Behrens, T.E., Berg, H.J., Jbabdi, S., Rushworth, M.F., Woolrich, M.W.: Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? Neuroimage 34(1), 144–155 (2007)

    Article  Google Scholar 

  3. Cox, R.W.: AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29(3), 162–173 (1996)

    Article  Google Scholar 

  4. Craddock, C., et al.: Towards automated analysis of connectomes: the configurable pipeline for the analysis of connectomes (C-PAC). Front Neuroinform. 42 (2013)

    Google Scholar 

  5. Di Martino, A., et al.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol. Psychiatry 19(6), 659 (2014)

    Article  Google Scholar 

  6. Dinov, I., et al.: Efficient, distributed and interactive neuroimaging data analysis using the LONI pipeline. Front. Neuroinform. 3, 22 (2009)

    Article  Google Scholar 

  7. Dinov, I.D., et al.: High-throughput neuroimaging-genetics computational infrastructure. Front. Neuroinform. 8, 41 (2014)

    Article  Google Scholar 

  8. Fischl, B.: Freesurfer. Neuroimage 62(2), 774–781 (2012)

    Article  Google Scholar 

  9. Gorgolewski, K.J., et al.: The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci. Data 3, 160044 (2016)

    Article  Google Scholar 

  10. Jack Jr., C.R., et al.: The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. J. Magn. Reson. Imaging: Off. J. Int. Soc. Magn. Reson. Med. 27(4), 685–691 (2008)

    Article  Google Scholar 

  11. Jenkinson, M., Beckmann, C.F., Behrens, T.E., Woolrich, M.W., Smith, S.M.: FSL. Neuroimage 62(2), 782–790 (2012)

    Article  Google Scholar 

  12. Lella, E., et al.: Communicability characterization of structural DWI subcortical networks in Alzheimer’s disease. Entropy 21(5), 475 (2019)

    Article  Google Scholar 

  13. Lella, E., et al.: Communicability disruption in Alzheimer’s diseaseconnectivity networks. J. Complex Netw. 7(1), 83–100 (2018)

    Article  MathSciNet  Google Scholar 

  14. Lombardi, A., et al.: Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes. NeuroImage 195, 150–164 (2019)

    Article  Google Scholar 

  15. Maglietta, R., et al.: Automated hippocampal segmentation in 3D MRI using random undersampling with boosting algorithm. Pattern Anal. Appl. 19(2), 579–591 (2016)

    Article  MathSciNet  Google Scholar 

  16. Penny, W.D., Friston, K.J., Ashburner, J.T., Kiebel, S.J., Nichols, T.E.: Statistical Parametric Mapping: The Analysis of Functional Brain Images. Elsevier, Amsterdam (2011)

    Google Scholar 

  17. Poldrack, R.A., Gorgolewski, K.J.: Making big data open: data sharing in neuroimaging. Nat. Neurosci. 17(11), 1510 (2014)

    Article  Google Scholar 

  18. Tournier, J.D., Calamante, F., Connelly, A.: MRtrix: diffusion tractography in crossing fiber regions. Int. J. Imaging Syst. Technol. 22(1), 53–66 (2012)

    Article  Google Scholar 

  19. Van Horn, J.D., Toga, A.W.: Human neuroimaging as a “big data” science. Brain Imaging Behav. 8(2), 323–331 (2014)

    Article  Google Scholar 

  20. Zuo, X.N., et al.: An open science resource for establishing reliability and reproducibility in functional connectomics. Sci. Data 1, 140049 (2014)

    Article  Google Scholar 

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Correspondence to Angela Lombardi .

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Lombardi, A. et al. (2019). Multidimensional Neuroimaging Processing in ReCaS Datacenter. In: Montella, R., Ciaramella, A., Fortino, G., Guerrieri, A., Liotta, A. (eds) Internet and Distributed Computing Systems . IDCS 2019. Lecture Notes in Computer Science(), vol 11874. Springer, Cham. https://doi.org/10.1007/978-3-030-34914-1_44

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  • DOI: https://doi.org/10.1007/978-3-030-34914-1_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34913-4

  • Online ISBN: 978-3-030-34914-1

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