BrkRaw
Update BrkRaw for Python 3.9+ and Modern Library Support
Is your feature request related to a problem? Please describe. We've been using BrkRaw to convert Bruker data to NIFTI under ParaVision 6 and CentOS 7 for years. Recently, we upgraded to ParaVision360 3.6 and AlmaLinux 9. Since ParaVision 360 now supports native NIFTI export, we hadn’t installed BrkRaw until we needed to read 2dseq data directly with Python. At that point, we discovered that BrkRaw does not support Python 3.9 on AlmaLinux 9, and many of its dependencies are outdated and difficult to manage.
Describe the solution you'd like We’d love to see BrkRaw updated to support Python 3.9 and newer Python libraries. The tool can focus on reading ParaVision360 2dseq files, while NIFTI and BIDS conversion could be handled by ParaVision360 and other specialized tools.
Describe alternatives you've considered It would be great for BrkRaw to support Python 3.13 and up-to-date libraries such as nibabel 5.3.2 and numpy 2.0.2.
Additional context I found an alternative way to load 2dseq files: https://github.com/isi-nmr/brukerapi-python
Bruker has provided ParaVision 360 version 3.5 and 3.6 phantom datasets for testing and compatibility checks. These datasets serve as excellent resources for developers and researchers to ensure software compatibility and data processing integrity.
Anyone interested can download these datasets after a simple registration process:
Download Bruker ParaVision Standard Datasets
Below is a table of the datasets currently available for download from the provided link.
| Modality | Method | Protocol | Comment | pv360-3-5 | pv360-3-6 |
|---|---|---|---|---|---|
| MRI | FLASH | T1_FLASH | 2D, Slices = 9, PVM_Matrix= 384x384, Acceleration info: PVM_EncZf=1.34 1.34, PVM_EncPft~ 1.55 1, PVM_EncMatrix=200 288, PVM_EncPftAlgorithm=Pocs | Download | Download |
| MRI | FLASH | T1_FLASH_3D | 3D, PVM_Matrix= 320x320x64, Acceleration info: PVM_EncZf=1 1 1, PVM_EncPft~ 1.15 1 1, PVM_EncMatrix=278 320 71, PVM_AntiAlias=1 1 ~1.11, PVM_EncPftAlgorithm=Zerofilling | Download | - |
| MRI | RARE | T2_TurboRARE | 2D, Slices = 9, PVM_Matrix= 256x256, Acceleration info: N.A. | Download | Download |
| MRI | RARE | T1_RARE | 2D, Slices = 9, PVM_Matrix= 256x256, Acceleration info: N.A. | Download | Download |
| MRI | MSME | T2map_MSME | 2D, Slices = 5, PVM_Matrix= 192x192, Acceleration info: N.A. | Download | Download |
| MRI | MGE | T2star_map_MGE | 2D, Slices = 1, PVM_Matrix= 256x256, Acceleration info: PVM_EncZf=1 1, PVM_EncPft= 1 ~1.33, PVM_EncMatrix=256 192, PVM_EncPftAlgorithm=Zerofilling | Download | Download |
| MRI | EPI | T2star_FID_EPI | 2D, Slices = 1, PVM_Matrix= 128x96, Acceleration info: PVM_EncZf=1 1, PVM_EncPft= 1 1.2, PVM_EncMatrix=128 80, PVM_EncPftAlgorithm=Zerofilling | Download | Download |
| MRI | EPIDTI | DTI_EPI_seg_30dir_sat | 2D, Slices = 5, PVM_Matrix = 128 128, NSegments=4, PVM_DwNDiffDir=30, PVM_DwNShells=1, Acceleration info: PVM_EncZf=1 1, PVM_EncPft= 1 1.6, PVM_EncMatrix=128 80, PVM_EncPftAlgorithm=Pocs | Download | Download |
| MRI | EPIDTI | DTI_EPI_seg_30dir_sat_multi | 2D, Slices = 5, PVM_Matrix = 128 128, NSegments=4, PVM_DwNDiffDir=30, PVM_DwNShells=1, Acceleration info: PVM_EncZf=1 1, PVM_EncPft= 1 1.6, PVM_EncMatrix=128 80, PVM_EncPftAlgorithm=Pocs | Download | Download |
| MRI | UTE3D | UTE3D | 3D, PVM_Matrix= 128x128x128, Acceleration info: N.A. | Download | Download |
| MRS | PRESS | PRESS_1H | Single Voxel Spectroscopy, 1H, PVM_SpecMatrix=2048 | Download | Download |
| MRI | FLASH | T1_FLASH_3D_iso | 3D, PVM_Matrix= 160x160x96, Acceleration info: PVM_EncZf=1 1 1, PVM_EncPft 1 1 1, PVM_EncMatrix=160 160 106, PVM_AntiAlias=1 1 ~1.11, PVM_EncPftAlgorithm=N.A. | - | Download |
| MRI | MGE | T2star_map_MGE_mod_pos | 2D, Slices = 1, PVM_Matrix= 256x256, Acceleration info: N.A., EchoAcqMode=positiveReadOutEchoes | Download | Download |
| MRI | MGE | T2star_map_MGE_mod_all | 2D, Slices = 1, PVM_Matrix= 256x256, Acceleration info: N.A., EchoAcqMode=allEchoes | Download | Download |
I’ve created a repository hosting the above Standard MRI phantom datasets for Bruker ParaVision 360 (version 3.6). The collection includes 14 image sequences with files in multiple formats—k-space, reconstructed data, headers, DICOM, and NIfTI—to support developers in testing and validating their code. https://github.com/cecilyen/PV360_StdData