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MNI 7T DICOM to BIDS converter

This project is the MNI 7T DICOM to BIDS converter, which is used at the Montreal Neurological Institute-Hospital to convert 7 Tesla DICOM scans to BIDS.

Installation

PIP

To install the converter with PIP, install the following packages in the relevant Python environment:

pip install git+https://github.com/BIC-MNI/BIC_MRI_pipeline_util
pip install git+https://github.com/BIC-MNI/MNI_7T_DICOM_to_BIDS

You must also have dcm2niix (preferably a more recent version) installed on your machine.

Docker

To install the converter with Docker, clone the GitHub repository and build the project using the run.Dockerfile file:

git clone https://github.com/BIC-MNI/MNI_7T_DICOM_to_BIDS mni_7t_dicom_to_bids
docker build -t mni_7t_dicom_to_bids -f mni_7t_dicom_to_bids/run.Dockerfile mni_7t_dicom_to_bids

Execution

You can run the MNI 7T DICOM to BIDS converter using the following command:

mni7t_dcm2bids <dicom_study_path> <bids_dataset_path> --subject <subject_label> --session <session_label>

The input DICOM directory must contain the DICOMs of a single session. The output BIDS directory can either be an empty directory (which can be created by the script) or be an existing BIDS directory (in which case the converted session is added to the existing BIDS).

BIDS naming dictionary

Anatomical

N 7T Terra Siemens acquisition BIDS Directory
1 anat-T1w_acq_mprage_0.8mm_CSptx T1w anat
2 anat-T1w_acq-mp2rage_0.7mm_CSptx_INV1 inv-1_MP2RAGE anat
3 anat-T1w_acq-mp2rage_0.7mm_CSptx_INV2 inv-2_MP2RAGE anat
4 anat-T1w_acq-mp2rage_0.7mm_CSptx_T1_Images T1map anat
5 anat-T1w_acq-mp2rage_0.7mm_CSptx_UNI_Images UNIT1 anat
6 anat-T1w_acq-mp2rage_0.7mm_CSptx_UNI-DEN desc-denoised_UNIT1 anat
7 anat-flair_acq-0p7iso_UPAdia FLAIR anat
8 CLEAR-SWI_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-SWI_T2starw anat
9 Romeo_P_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-romeo_T2starw anat
10 Romeo_Mask_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-romeo_desc-mask_T2starw anat
11 Romeo_B0_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-romeo_desc-unwrapped_T2starw anat
12 Aspire_M_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-aspire_part-mag_T2starw anat
13 Aspire_P_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-aspire_part-phase_T2starw anat
14 EchoCombined_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-aspire_desc-echoCombined_T2starw anat
15 sensitivity_corrected_mag_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-aspire_desc-echoCombinedSensitivityCorrected_T2starw anat
16 T2star_anat-T2star_acq-me_gre_0*7iso_ASPIRE acq-aspire_[T2starw,T2starmap] anat
17 anat-mtw_acq-MTON_07mm acq-mtw_mt-on_MTR anat
18 anat-mtw_acq-MTOFF_07mm acq-mtw_mt-off_MTR anat
19 anat-mtw_acq-T1w_07mm acq-mtw_T1w anat
20 anat-nm_acq-MTboost_sag_0.55mm acq-neuromelaninMTw_T1w anat
21 anat-angio_acq-tof_03mm_inplane angio anat
22 anat-angio_acq-tof_03mm_inplane_MIP_SAG acq-sag_angio anat
23 anat-angio_acq-tof_03mm_inplane_MIP_COR acq-cor_angio anat
24 anat-angio_acq-tof_03mm_inplane_MIP_TRA acq-tra_angio anat

The acquisitions acq-romeo_part-phase_T2starw, acq-aspire_part-mag_T2starw, and acq-aspire_part-phase_T2starw each have five echoes. The final string will include the identifier echo- followed by the echo number. For example: acq-aspire_echo-1_part-mag_T2starw.

Field maps

N 7T Terra Siemens acquisition BIDS Directory
1 fmap-b1_tra_p2 acq-[anat,sfam]_TB1TFL fmap
2 fmap-b1_acq-sag_p2 acq-[anat,sfam]_TB1TFL fmap
3 fmap-fmri_acq-mbep2d_SE_19mm_dir-AP acq-fmri_dir-AP_epi fmap
4 fmap-fmri_acq-mbep2d_SE_19mm_dir-PA acq-fmri_dir-PA_epi fmap

Functional

N 7T Terra Siemens acquisition BIDS Directory
1 func-cross_acq-ep2d_MJC_19mm task-rest_bold func
2 func-cloudy_acq-ep2d_MJC_19mm task-cloudy_bold func
3 func-present_acq-mbep2d_ME_19mm task-present_bold func

Each functional MRI acquisition includes three echoes and a phase. The final string will contain the identifier echo- followed by the echo number (e.g., task-rest_echo-1_bold). Additionally, the string part-phase will be included to identify the phase (e.g., task-rest_echo-1_part-phase_bold).

Diffusion weighted images

N 7T Terra Siemens acquisition BIDS Directory
1 *dwi_acq_b0_PA acq-b0_dir-PA_dwi dwi
2 *dwi_acq_b0_PA_SBRef acq-b0_dir-PA_sbref dwi
3 *dwi_acq_multib_38dir_AP_acc9 acq-multib38_dir-AP_dwi dwi
4 *dwi_acq_multib_38dir_AP_acc9_SBRef acq-multib38_dir-AP_sbref dwi
5 *dwi_acq_multib_70dir_AP_acc9 acq-multib70_dir-AP_dwi dwi
6 *dwi_acq_multib_70dir_AP_acc9_SBRef acq-multib70_dir-AP_sbref dwi

The string part-phase will be included to identify the phase acquisitions (e.g., acq-multib38_dir-AP_part-phase_dwi).

Abbreviation Glossary

Abbreviation Description
AP Anterio-Posterior
PA Postero-anterior
mtw Magnetic transfer weighted
sfmap Scaled flip angle map
tof Time of flight
multib Multi shell N directions
semphon Semantic-phonetic
romeo Rapid opensource minimum spanning tree algorithm
aspire Combination of multi-channel phase data from multi-echo acquisitions

References

  1. Eckstein K, Dymerska B, Bachrata B, Bogner W, Poljanc K, Trattnig S, Robinson SD. Computationally efficient combination of multi‐channel phase data from multi‐echo acquisitions (ASPIRE). Magnetic resonance in medicine. 2018 Jun;79(6):2996-3006. https://doi.org/10.1002/mrm.26963

  2. Dymerska B, Eckstein K, Bachrata B, Siow B, Trattnig S, Shmueli K, Robinson SD. Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO). Magnetic resonance in medicine. 2021 Apr;85(4):2294-308. https://doi.org/10.1002/mrm.28563

  3. Sasaki M, Shibata E, Tohyama K, Takahashi J, Otsuka K, Tsuchiya K, Takahashi S, Ehara S, Terayama Y, Sakai A. Neuromelanin magnetic resonance imaging of locus ceruleus and substantia nigra in Parkinson's disease. Neuroreport. 2006 Jul 31;17(11):1215-8. https://doi.org/10.1097/01.wnr.0000227984.84927.a7

Compilation

This project can be compiled and distributed as an executable using PyInstaller, the compilation process is described in the COMPILATION.md file.

Related repositories

This DICOM to BIDS converter is a rewrite of Raul Cruces' MPN 7T pipeline DICOM to BIDS converter. The present converter aims to provide a similar behavior (up to versions) with enhanced safety checks, portability, performance, and maintainability.

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