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. 2024;9(99):5839.
doi: 10.21105/joss.05839. Epub 2024 Jul 3.

HeuDiConv - flexible DICOM conversion into structured directory layouts

Affiliations

HeuDiConv - flexible DICOM conversion into structured directory layouts

Yaroslav O Halchenko et al. J Open Source Softw. 2024.
No abstract available

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Figures

Figure 1:
Figure 1:. HeuDiConv automates the keystone conversion step in reproducible data handling, without compromising operator flexibility.
The showcased set-up depicts a 2-machine infrastructure, with heudiconv operating on the same machine as subsequent analysis steps for data in a standardized and shareable representation. For more advanced usage at institutions with dedicated infrastructure, HeuDiConv can operate on an additional third machine, which then interfaces between the depicted two machines and is dedicated to data repositing, versioning, and backup.
Figure 2:
Figure 2:. HeuDiConv conversion and layout is controlled via heuristics (custom or provided built-ins) either with manual tune up of proposed filenames or fully automated.
The heudiconv application can be used with the -c none parameter to generate by heuristic a list of filenames for the user to edit, before invoking the conversion to be performed via the -c dcm2niix option to use the dcm2niix tool. The process is idempotent, and specifying the -c dcm2niix option can automatically convert without seeking user tune up of proposed filenames.
Figure 3:
Figure 3:. Downloads experienced an initial sharp rise after the ReproNim HeuDiconv training event at OHBM in mid 2018, and have subsequently followed a positive trend along with the usage — exceeding 1000 sessions per week — in the data collection interval.
Depicted are weekly download and confirmed session estimates, averaged per month, with a 95% confidence interval. User session estimates for July and August 2022 are linearly extrapolated from the nearest neighbour. Download counts are sourced from PyPI, the Python community repository; whereas user session counts are sourced from Etelemetry, an infrastructure for verifiable research impact, which end-users can disable to protect privacy.

References

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