This title appears in the Scientific Report :
2019
Please use the identifier:
http://hdl.handle.net/2128/22468 in citations.
Please use the identifier: http://dx.doi.org/10.3389/fninf.2019.00042 in citations.
Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri)
Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri)
Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution mi...
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Personal Name(s): | Pallast, Niklas |
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Diedenhofen, Michael / Blaschke, Stefan / Wieters, Frederique / Wiedermann, Dirk / Hoehn, Mathias / Fink, Gereon R. / Aswendt, Markus (Corresponding author) | |
Contributing Institute: |
Kognitive Neurowissenschaften; INM-3 |
Published in: | Frontiers in neuroinformatics, 13 (2019) S. 42 |
Imprint: |
Lausanne
Frontiers Research Foundation
2019
|
PubMed ID: |
31231202 |
DOI: |
10.3389/fninf.2019.00042 |
Document Type: |
Journal Article |
Research Program: |
(Dys-)function and Plasticity |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.3389/fninf.2019.00042 in citations.
Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies. |