首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services
  • 本地全文:下载
  • 作者:Paolo Avesani ; Brent McPherson ; Soichi Hayashi
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2019
  • 卷号:6
  • DOI:10.1038/s41597-019-0073-y
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:We describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structural connectome construction). The O3D open services can allow cognitive and clinical neuroscientists to run the connectome mapping algorithms on new, user-uploaded, data. Open source code implementing all O3D services is also provided to allow computational and computer scientists to reuse and extend the processing methods. Publishing both data-derivatives and integrated processing pipeline promotes practices for scientific reproducibility and data upcycling by providing open access to the research assets for utilization by multiple scientific communities.
国家哲学社会科学文献中心版权所有