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Neuroconductor: an R platform for medical imaging analysis
John Muschelli1, Adrian Gherman1, Jean-Philippe Fortin2
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, USA.
Biostatistics (Oxford, England)
|January 12, 2018
Summary
Neuroconductor is an open-source R platform for reproducible computational imaging software. It offers a central repository, rapid updates, training, and quality control to enhance image data analysis reproducibility.
Area of Science:
- Computational imaging
- Bioinformatics
- Scientific software development
Background:
- Computational imaging software is crucial for data analysis.
- Disseminating and maintaining such software presents challenges.
- Reproducibility in image data analysis is a significant concern.
Purpose of the Study:
- To introduce Neuroconductor, an open-source platform for R-based computational imaging software.
- To detail the platform's goals: repository, rapid dissemination, community training, quality control, and reproducibility.
- To describe the user and developer experience within the Neuroconductor ecosystem.
Main Methods:
- Neuroconductor is built on the R programming language.
- It hosts 51 interoperable R packages for various imaging analysis tasks.
- New packages undergo formal review and automated testing.
Main Results:
- The platform provides a centralized repository for R packages in imaging analysis.
- It facilitates rapid dissemination of software updates.
- Automated and manual quality controls are implemented to ensure software quality.
Conclusions:
- Neuroconductor enhances the quality and reproducibility of computational imaging software.
- It fosters a diverse community of scientists through training and resources.
- The platform streamlines the development and dissemination process for R packages in scientific imaging.
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