High-resolution Brain Image Registration on a Distributed Computing System in the Brain/MINDS Project
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1
RIKEN, Brain Science Institute (BS), Japan
For Neuroinformatics the era of big data presents a number of challenges for systematizing the collection, transferal and processing of brain related data. Specifically for neuroimaging there are hurdles for registering high-resolution brain images (2D/3D or 4D) in a timely manner - a task that is important for normalizing between different imaging systems and to make comparative studies in a common space. Thus, time and space requirements mean that processing data on a single computer may not be possible.
For the Brain/MINDS project, which studies the brain of the common marmoset (Callithrix jacchus), and at the Neuroinformatics Japan Center (NIJC), we have developed a data analysis platform that combines a high performance computer cluster (HPC) with a large-scale storage system (LSSS), running over a high-speed network. A virtual machine (VM) running Ubuntu, via VDI technology, provides seamless access to the HPC and LSSS. Users can therefore perform data analysis and processing on data sizes that would exceed the capabilities of their desktop computers.
To facilitate distributed computation we have developed a Python package called SPyKGD that uses Open Grid Scheduler/Grid Engine and makes it simple to submit jobs to the cluster computer. By using SPyKGD with the Jupyter Notebook web application users can easily create new workflows, save the state of their calculations within the notebook itself, and share them with other users.
Currently we are using this platform to process and register high-resolution multi-modal marmoset brain data (histology, MRI, etc.) to reconstruct the brain in 3D. To do this we launch a number of jobs on the cluster for image processing, linear, and non-linear image registration. We will describe the platform’s architecture, example workflows and registration results.
Acknowledgements
This research is supported by the program for Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) from Japan Agency for Medical Research and development, AMED.
References
Okano H, Mitra P. Brain-mapping projects using the common marmoset. Neurosci Res. 2015 Apr;93:3-7. doi: 10.1016/j.neures.2014.08.014
Keywords:
image registration,
marmoset,
big data,
HPC,
jupyter notebook
Conference:
Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 Sep, 2016.
Presentation Type:
Poster
Topic:
Computing systems
Citation:
Woodward
A,
Maeda
M,
Takeuchi
T,
Oka
H,
Morii
Y,
Okumura
Y,
Hashikawa
T and
Yamaguchi
Y
(2016). High-resolution Brain Image Registration on a Distributed Computing System in the Brain/MINDS Project.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2016.
doi: 10.3389/conf.fninf.2016.20.00047
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Received:
30 Apr 2016;
Published Online:
18 Jul 2016.
*
Correspondence:
Dr. Alexander Woodward, RIKEN, Brain Science Institute (BS), Wako, Saitama, 351-0198, Japan, alexander.woodward@riken.jp