Preprint Review Version 2 Preserved in Portico This version is not peer-reviewed

The Pipeline of Processing fMRI Data with Python Based on the Ecosystem NeuroDebian

Version 1 : Received: 31 March 2019 / Approved: 2 April 2019 / Online: 2 April 2019 (07:39:13 CEST)
Version 2 : Received: 3 April 2019 / Approved: 8 April 2019 / Online: 8 April 2019 (05:46:55 CEST)

How to cite: Li, Q.; Xue, R. The Pipeline of Processing fMRI Data with Python Based on the Ecosystem NeuroDebian. Preprints 2019, 2019040027. https://doi.org/10.20944/preprints201904.0027.v2 Li, Q.; Xue, R. The Pipeline of Processing fMRI Data with Python Based on the Ecosystem NeuroDebian. Preprints 2019, 2019040027. https://doi.org/10.20944/preprints201904.0027.v2

Abstract

In the neuroscience research field, specific for medical imaging analysis, how to mining more latent medical information from big medical data is significant for us to find the solution of diseases. In this review, we focus on neuroimaging data that is functional Magnetic Resonance Imaging (fMRI) which non-invasive techniques, it already becomes popular tools in the clinical neuroscience and functional cognitive science research. After we get fMRI data, we actually have various software and computer programming that including open source and commercial, it's very hard to choose the best software to analyze data. What's worse, it would cause final result imbalance and unstable when we combine more than software together, so that's why we want to make a pipeline to analyze data. On the other hand, with the growing of machine learning, Python has already become one of very hot and popular computer programming. In addition, it is an open source and dynamic computer programming, the communities, libraries and contributors fast increase in the recent year. Through this review, we hope that can make neuroimaging data analysis more easy, stable and uniform base the one platform system.

Keywords

neuroscience; big data; functional Magnetic Resonance (fMRI); pipeline; one platform system

Subject

Computer Science and Mathematics, Analysis

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