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Data Curation for Preclinical and Clinical Multimodal Imaging Studies.

Grace Gyamfuah Yamoah1, Liji Cao2, Chao Wu Wu3,4

  • 1Institute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany.

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Summary

A new secure file format standardizes multimodal imaging data in research. This format compresses data, ensuring security and efficient storage for advanced biomedical imaging analysis.

Keywords:
CompressionCredibilityCryptographic hashingData curationFile formatMetadataMultimodal imagingReproducibilitySerializationTimestamp

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Area of Science:

  • Biomedical imaging research
  • Data science in medicine
  • Medical informatics

Background:

  • Clinical medical imaging has established data storage standards.
  • Biomedical research currently lacks standardized data curation for imaging studies.
  • Developing such standards is crucial for advancing diagnostic and theranostic approaches.

Purpose of the Study:

  • To develop a free, secure file format for multimodal biomedical imaging data.
  • To support common in vivo imaging modalities up to five dimensions.
  • To establish data curation standards for biomedical research.

Main Methods:

  • Implemented lossless compression and cryptographic hashing for image slices.
  • Utilized parallel processing to accelerate hash computations.
  • Developed a C++ implementation tested on multimodal data from six imaging sites and integrated into analysis software.

Main Results:

  • Achieved approximately 50% storage space reduction for micro-CT data.
  • Parallelization improved hash computation speed by a factor of 4.
  • Demonstrated a compression rate of 137 MB/s for a 354 MB file.

Conclusions:

  • The developed file format is a step towards standardized data abstraction and curation in preclinical and clinical multimodal imaging.
  • This work improves the interface between multimodal imaging modalities and analysis software.