Neuroconductor is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: provide a centralized repository of R software dedicated to image analysis; disseminate quickly software updates; educate a large, diverse community of scientists using detailed tutorials and short courses; ensure quality via automatic and manual quality controls; and promote reproducibility of image data analysis. Based on the programming language R, Neuroconductor started 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.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Athanasia M. Mowinckel, Didac Vidal-Piñeiro: Visualisation of Brain Statistics with R-packages ggseg and ggseg3d (2019) arXiv
- Polzehl, Jörg; Tabelow, Karsten: Magnetic resonance brain imaging. Modeling and data analysis using R (2019)
- Smirnova, Ekaterina; Ivanescu, Andrada; Bai, Jiawei; Crainiceanu, Ciprian M.: A practical guide to big data (2018)