highspeed-mriqc-docs.Rmd 1.9 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647
  1. ```{r, echo=FALSE, message=FALSE, include=FALSE}
  2. if (!requireNamespace("pacman")) install.packages("pacman")
  3. packages_cran <- c("here")
  4. pacman::p_load(char = packages_cran)
  5. if (basename(here::here()) == "highspeed"){
  6. path_root = here::here("highspeed-mriqc")
  7. } else {
  8. path_root = here::here()
  9. }
  10. ```
  11. ## MRI quality control
  12. #### Overview
  13. > MRIQC extracts no-reference IQMs (image quality metrics) from structural (T1w and T2w) and functional MRI (magnetic resonance imaging) data.
  14. Please see the [official MRIQC documentation](https://mriqc.readthedocs.io/en/stable/) for details and refer to the paper listed in the References section.
  15. #### Container: `mriqc` container, version 0.15.2rc1
  16. MRIQC quality control was performed using [`mriqc`](https://mriqc.readthedocs.io/en/stable/), version 0.15.2rc1
  17. ``` bash
  18. singularity pull docker://poldracklab/mriqc:0.15.2rc1
  19. ```
  20. #### MRIQC subject-level reports: `highspeed-mriqc-subject-level.sh`
  21. First, MRIQC has to run on the individual subject-, (if available, session-), modality- and run- level.
  22. This is achieved by running the `highspeed-mriqc-subject-level.sh` shell-script.
  23. The script is parallelizing all subjects, sessions, modalities and runs on the cluster.
  24. ```{bash, echo=TRUE, code=readLines(file.path(path_root, "code", "mriqc", "highspeed-mriqc-subject-level.sh")), eval=FALSE}
  25. ```
  26. #### MRIQC group-level reports: `highspeed-mriqc-group-level.sh`
  27. Afterwards, one can run the `highspeed-mriqc-group-level.sh` script to acquire group statistics of the quality metrics.
  28. ```{bash, echo=TRUE, code=readLines(file.path(path_root, "code", "mriqc", "highspeed-mriqc-group-level.sh")), eval=FALSE}
  29. ```
  30. #### References
  31. > Esteban, O., Birman, D., Schaer, M., Koyejo, O. O., Poldrack, R. A., & Gorgolewski, K. J. (2017). MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites. PLoS ONE, 12(9), e0184661. [doi: 10.1371/journal.pone.0184661](https://doi.org/10.1371/journal.pone.0184661)