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Neuroconductor: An R Platform for Medical Imaging Analysis
Biostatistics (2017)
  • John Muschelli, III
  • Jean-Philippe Fortin, Johns Hopkins Bloomberg School of Public Health
  • Adrian Gherman, Johns Hopkins University
  • Brian Avants, University of Pennsylvania
  • Brandon Whitcher, Imperial College London
  • Jonathan D Clayden, University College London
  • Brian S. Caffo, PhD, Johns Hopkins Bloomberg School of Public Health
  • Ciprian Crainiceanu, PhD, Johns Hopkins Bloomberg School of Public Health
Abstract
Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: 1) provide a centralized repository of R software dedicated to image analysis, 2) disseminate software updates quickly, 3) train a large, diverse community of scientists using detailed tutorials and short courses, 4) increase software quality via automatic and manual quality controls, and 5) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of Neuroconductor’s purpose and the user and developer experience. 
Keywords
  • neuroimaging,
  • imaging,
  • r
Publication Date
Fall 2017
Citation Information
John Muschelli, Jean-Philippe Fortin, Adrian Gherman, Brian Avants, et al.. "Neuroconductor: An R Platform for Medical Imaging Analysis" Biostatistics (2017)
Available at: http://works.bepress.com/john_muschelli/6/
Creative Commons license
Creative Commons License
This work is licensed under a Creative Commons CC_BY-NC-SA International License.