%0 Journal Article %T The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research %A Wojtek J. Goscinski %A Paul McIntosh %A Christopher J. Hall %A Darren Thompson %A Graham Galloway %A Neil E. B. Killeen %A Parnesh Raniga %A Amanda Ng %A Govinda Poudel %A David G. Barnes %A Toan Nguyen %A Paul Bonnington %A Gary F. Egan %J Frontiers in Neuroinformatics %D 2014 %I Frontiers Media %R 10.3389/fninf.2014.00030 %X The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. %K neuroinformatics infrastructure %K high performance computing %K instrument integration %K CT reconstruction %K cloud computing %K Huntington's disease %K Quantitative susceptibility mapping %K digital atlasing %U http://www.frontiersin.org/Journal/10.3389/fninf.2014.00030/abstract