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Working with the DICOM and NIfTI Data Standards in R

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  • Whitcher, Brandon
  • Schmid, Volker J.
  • Thorton, Andrew

Abstract

Two packages, oro.dicom and oro.nifti, are provided for the interaction with and manipulation of medical imaging data that conform to the DICOM standard or ANALYZE/NIfTI formats. DICOM data, from a single file or directory tree, may be uploaded into R using basic data structures: a data frame for the header information and a matrix for the image data. A list structure is used to organize multiple DICOM files. The S4 class framework is used to develop basic ANALYZE and NIfTI classes, where NIfTI extensions may be used to extend the fixed-byte NIfTI header. One example of this, that has been implemented, is an XML-based “audit trail” tracking the history of operations applied to a data set. The conversion from DICOM to ANALYZE/NIfTI is straightforward using the capabilities of both packages. The S4 classes have been developed to provide a userfriendly interface to the ANALYZE/NIfTI data formats; allowing easy data input, data output, image processing and visualization.

Suggested Citation

  • Whitcher, Brandon & Schmid, Volker J. & Thorton, Andrew, 2011. "Working with the DICOM and NIfTI Data Standards in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 44(i06).
    • Handle: RePEc:jss:jstsof:v:044:i06
    DOI: http://hdl.handle.net/10.18637/jss.v044.i06
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    1. repec:jss:jstsof:44:i09 is not listed on IDEAS
    2. Loïc Labache & Tian Ge & B. T. Thomas Yeo & Avram J. Holmes, 2023. "Language network lateralization is reflected throughout the macroscale functional organization of cortex," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. repec:jss:jstsof:44:i11 is not listed on IDEAS
    4. Léonie Geissmann & David Coynel & Andreas Papassotiropoulos & Dominique J. F. Quervain, 2023. "Neurofunctional underpinnings of individual differences in visual episodic memory performance," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Cardona Jiménez, Johnatan & de B. Pereira, Carlos A., 2021. "Assessing dynamic effects on a Bayesian matrix-variate dynamic linear model: An application to task-based fMRI data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 163(C).
    6. repec:jss:jstsof:44:i01 is not listed on IDEAS
    7. repec:jss:jstsof:44:i06 is not listed on IDEAS
    8. repec:jss:jstsof:44:i12 is not listed on IDEAS

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