Recent advancements in optical microscopy and specimen preparation have greatly improved the specificity and sensitivity of observation. Imaging instruments have become readily available and produce data at GB/s rates. These capabilities now allow capture of large numbers of whole-brain volumetric datasets, enabling morphological study including connectivity within the brain. Brain image datasets pose a problem for data storage, access, and analysis due to their large and complex structure.

The Brain Image Library (BIL) is a national public resource of brain image datasets contributed by the brain research community. BIL is located at the Pittsburgh Supercomputing Center (PSC). To manage metadata associated with brain image collections, BIL uses iRODS, an open source data management system. This paper describes the use of iRODS for data management within the Brain Image Library an NIH BRAIN Initiative-funded petascale archive of spatial brain datasets.

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Pham KLee SCho SKim SSon Y(2022)A Survey on Data Management using Integrated Rule-Oriented Data System2022 13th International Conference on Information and Communication Technology Convergence (ICTC)10.1109/ICTC55196.2022.9953028(1116-1118)Online publication date: 19-Oct-2022
https://doi.org/10.1109/ICTC55196.2022.9953028
Miller MFan JTward D(2021)Multi scale diffeomorphic metric mapping of spatial transcriptomics datasets2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW53098.2021.00504(4467-4475)Online publication date: Jun-2021
https://doi.org/10.1109/CVPRW53098.2021.00504
Shah ZAnjum AAbouelhoda M(2019)Modelling Genomics Datasets to Optimize Its Usage Patterns for Efficient AnalyticsProceedings of the 3rd International Conference on Advances in Artificial Intelligence10.1145/3369114.3369148(135-140)Online publication date: 26-Oct-2019
https://dl.acm.org/doi/10.1145/3369114.3369148

Index Terms

Applying iRODS to the Brain Image Library
1. Applied computing
  1. Life and medical sciences
    1. Computational biology
      1. Imaging
2. Information systems
  1. Information systems applications
    1. Digital libraries and archives
    2. Multimedia information systems
      1. Multimedia databases

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PEARC '18: Proceedings of the Practice and Experience on Advanced Research Computing: Seamless Creativity

July 2018

652 pages

ISBN:9781450364461

DOI:10.1145/3219104

General Chair:
Sergiu Sanielevici
Pittsburgh Supercomputing Center

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 22 July 2018

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PEARC '18: Practice and Experience in Advanced Research Computing

July 22 - 26, 2018

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PEARC '18 Paper Acceptance Rate 79 of 123 submissions, 64%;

Overall Acceptance Rate 133 of 202 submissions, 66%

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Pham KLee SCho SKim SSon Y(2022)A Survey on Data Management using Integrated Rule-Oriented Data System2022 13th International Conference on Information and Communication Technology Convergence (ICTC)10.1109/ICTC55196.2022.9953028(1116-1118)Online publication date: 19-Oct-2022
https://doi.org/10.1109/ICTC55196.2022.9953028
Miller MFan JTward D(2021)Multi scale diffeomorphic metric mapping of spatial transcriptomics datasets2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW53098.2021.00504(4467-4475)Online publication date: Jun-2021
https://doi.org/10.1109/CVPRW53098.2021.00504
Shah ZAnjum AAbouelhoda M(2019)Modelling Genomics Datasets to Optimize Its Usage Patterns for Efficient AnalyticsProceedings of the 3rd International Conference on Advances in Artificial Intelligence10.1145/3369114.3369148(135-140)Online publication date: 26-Oct-2019
https://dl.acm.org/doi/10.1145/3369114.3369148

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Extracting and Ingesting DDI Metadata and Digital Objects from a Data Archive into the iRODS Extension of the NARA TPAP Using the OAI-PMH

Efficient magnetic resonance brain image registration and high performance registration-based brain image segmentation

Multi-modality three-dimensional brain image registration and analysis

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