Paper Info
Title
Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).
Abstract
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.
Year
DOI
Venue
2019
10.3389/fninf.2019.00042
FRONTIERS IN NEUROINFORMATICS
Keywords
Field
DocType
processing pipeline,MRI,atlas registration,stroke,preclinical neuroimaging
Brain mapping,Neuroinformatics,Data mining,Brain atlas,Diffusion MRI,Pattern recognition,Computer science,Software,Artificial intelligence,Python (programming language),Image registration,Magnetic resonance imaging
Journal
Volume
ISSN
Citations 
13
1662-5196
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Niklas Pallast100.68
Diedenhofen Michael2225.09
Stefan Blaschke300.34
Frederique Wieters400.68
Dirk Wiedermann5797.17
M Hoehn6999.96
Gereon R. Fink741748.25
Markus Aswendt821.04