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R Markdown in het kort
R Markdown
R Markdown grew from the knitr and RStudio ecosystem and became the dominant reproducible-reporting format for R-centered data science before Quarto generalized the model across more languages.
DCM in het kort
DCM
DICOM grew out of the need to exchange imaging data across scanners, archives, and clinical systems without throwing away the surrounding context that makes a medical image usable in practice.
Formaatvergelijking
| Kenmerk | R Markdown | DCM |
|---|---|---|
| File type | Document | Image |
| Extensions |
|
|
| MIME type |
|
|
| Created year | 2012 | 1993 |
| Inventor | Yihui Xie (RStudio / knitr) | ACR-NEMA / DICOM Standards Committee |
| Status | active | active |
| Primary use cases |
|
|
| Vector scaling | Niet ondersteund | Niet ondersteund |
Wanneer je elk formaat gebruikt
When to use R Markdown
- Your source file is already in R Markdown.
- Preserve source expectations before exporting to DCM.
- R Markdown is commonly used in document workflows.
When to use DCM
- Your target workflow expects DCM.
- Improve delivery compatibility with DCM.
- DCM is commonly used in image workflows.
Veelgestelde vragen
Why convert R Markdown to DCM?
Convert to DCM when the output must remain part of a medical-imaging workflow, preserving both image data and associated study metadata.
It is the correct target for diagnostic, archival, and interoperable clinical imaging systems.
What changes when converting R Markdown to DCM?
This conversion changes how the format behaves in downstream tools and delivery environments.
What should I review after converting R Markdown to DCM?
Validate output quality on representative files and confirm the target format behaves correctly in the destination workflow.