VisN: Neuroimaging Toolkit for Medical Image Visualization

Abstract

Event Abstract Back to Event VisN: Neuroimaging Toolkit for Medical Image Visualization Justin S. Senseney1, 2*, Terry Oakes1 and Gerard Riedy1 1 National Intrepid Center of Excellence, Research Department, United States 2 National Institutes of Health, Center for Information Technology, United States The National Intrepid Center of Excellence (NICoE) performs patient care and research of traumatic brain injury (TBI) and related psychological health conditions for United States armed forces. This research includes multi-modal neuroimaging acquisitions that are not available in current clinical medicine. VisN has been developed to apply existing open-source image processing libraries to demonstrate the potential of next-generation radiology to aid in the understanding of mental health. VisN extends the open-source Medical Image Processing, Analysis, and Visualization (MIPAV) program and uses the ImageJ program (Schneider, 2012) developed at the National Institutes of Health to provide a PACS-like system to radiologists that provides memory management and distributed database access functionality not yet found in clinically oriented software. The result is a familiar interface for the radiologist, as in Figure 1, while still allowing the application of emerging image processing tools. VisN can apply transformation matrices and non-linear volumetric transformation maps ad-hoc to the medical image fusion process. Once overlaid, VisN can define statistical parameters of interest for the visualization of functional activations. Tractography information is available using Camino (Cook, 2006). Finally, regions of interest can be selected and visualized on a volumetric basis, as shown in Figure 2. This provides a focus on real-time image processing tools that are manipulated through an integrated interface shown in Figure 3. VisN provides an open-source framework for emerging neuroimaging needs in radiology software. NICoE’s imaging protocol combines clinically useful structural images with images that do not have an immediate clinical application but may provide useful research information. Research images include functional, diffusion, spectroscopy, susceptibility, and perfusion MRI studies. Fluorodeoxyglucose (FDG) positron emission tomography (PET) images, broad electroencephalography data, and spatially localized magnetoencephalography (MEG) are also available. These multi-modal, spatially variable image sets make it difficult for commercially available image processing systems to provide the flexibility needed to conduct this research. VisN advances the state of accessible image processing to provide a viable platform for advanced neuroimaging-related software which can easily be translated into a radiology environment. Figure 1 Figure 2 Figure 3 References Cook, P A, Y Bai, K K Seunarine, M G Hall, G J Parker, and D C Alexander. 2006. “Camino : Open-Source Diffusion-MRI Reconstruction and Processing.” In 14th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, 14:2759. Seattle, WA. Schneider, Caroline a, Wayne S Rasband, and Kevin W Eliceiri. 2012. “NIH Image to ImageJ: 25 Years of Image Analysis.” Nature Methods 9 (7) (June 28): 671–675. doi:10.1038/nmeth.2089. http://www.nature.com/doifinder/10.1038/nmeth.2089. Keywords: Traumatic brain injury (TBI), multi-modal neuroimaging, functional magnetic resonance imaging (fMRI), diffusion weighted imaging (DWI), Military Medicine Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013. Presentation Type: Poster Topic: Neuroimaging Citation: Senseney JS, Oakes T and Riedy G (2013). VisN: Neuroimaging Toolkit for Medical Image Visualization. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00090 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 08 Apr 2013; Published Online: 11 Jul 2013. * Correspondence: Mr. Justin S Senseney, National Intrepid Center of Excellence, Research Department, Bethesda, MD, 20899, United States, justin.senseney@nih.gov Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Justin S Senseney Terry Oakes Gerard Riedy Google Justin S Senseney Terry Oakes Gerard Riedy Google Scholar Justin S Senseney Terry Oakes Gerard Riedy PubMed Justin S Senseney Terry Oakes Gerard Riedy Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.