Open jsheunis opened 4 years ago
@jsheunis Could you please add in the main text:
Collaborators: David Meunier, Bastien Cagna, Régis Trapeau, Kep Kee Loh, Julien Sein, Sylvain Takerkart, Olivier Coulon, Pascal Belin
Many thanks
The title and abstract are correct. Thanks for adding the collaborators to the main text.
Slides corresponding to the OSR2020 presentation: https://docs.google.com/presentation/d/11RrcZW25MyLbc0_9T2zzhwy5RyUvcjYG4UAgzjuuv8M/edit?usp=sharing
Macapype: An open multi-software framework for non-human primate anatomical MRI processing
By David Meunier, Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, Marseille, France
Collaborators: David Meunier, Bastien Cagna, Régis Trapeau, Kep Kee Loh, Julien Sein, Sylvain Takerkart, Olivier Coulon, Pascal Belin
Abstract
Non-human primate (NHP) MRI neuroimaging is rapidly gaining prominence in neuroscience research as an essential means for comparing and bridging human and others primates brain anatomy and function. A key challenge that confronts the NHP neuroimaging community is the lack of standardized and robust pipelines for the processing of MRI data.
Macapype provides an open-source framework to create customized NHP-specific MRI data processing pipelines based on Nipype. Apart from the standard tools (AFNI, FSL, SPM12, and ANTs already available in Nipype), custom wraps, specific to NHP data processing such as the brain extraction AtlasBREX and registration between subject brain and the NMT macaque template, are available in the Macapype package. The user can flexibly construct customized pipelines, putting together the various processing modules (with desired parameters) that are optimal for their dataset.
A docker file is included in the package to allow users to get a fully embedded version of the pipelines.Pipelines are compatible with BIDS formatted input images. The pipelines achieve robust skull-stripping and segmentation on anatomical data from both macaque and marmoset datasets.
Installation procedures, API, and an extensive description of the segmentation results are available in the documentation.
Useful Links
https://github.com/Macatools/macapype https://macatools.github.io/macapype/index.html
Tagging @davidmeunier79