Bruker TIFF data conversion

Install NeuroConv with the additional dependencies necessary for reading Bruker TIFF data.

pip install "neuroconv[brukertiff]"

Convert single imaging plane

Convert Bruker TIFF imaging data to NWB using BrukerTiffSinglePlaneConverter.

>>> from zoneinfo import ZoneInfo
>>> from neuroconv.converters import BrukerTiffSinglePlaneConverter
>>>
>>> # The 'folder_path' is the path to the folder containing the OME-TIF image files and the XML configuration file.
>>> folder_path = OPHYS_DATA_PATH / "imaging_datasets" / "BrukerTif" / "NCCR32_2023_02_20_Into_the_void_t_series_baseline-000"
>>> converter = BrukerTiffSinglePlaneConverter(folder_path=folder_path)
>>>
>>> metadata = converter.get_metadata()
>>> # For data provenance we can add the time zone information to the conversion if missing
>>> session_start_time = metadata["NWBFile"]["session_start_time"]
>>> tzinfo = ZoneInfo("US/Pacific")
>>> metadata["NWBFile"].update(session_start_time=session_start_time.replace(tzinfo=tzinfo))
>>>
>>> # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{path_to_save_nwbfile}"
>>> converter.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata)

Convert multiple imaging planes

Convert volumetric Bruker TIFF imaging data to NWB using BrukerTiffMultiPlaneConverter. The plane_separation_type parameter defines how to load the imaging planes. Use “contiguous” to create the volumetric two photon series, and “disjoint” to create separate imaging plane and two photon series for each plane.

>>> from zoneinfo import ZoneInfo
>>> from neuroconv.converters import BrukerTiffMultiPlaneConverter
>>>
>>> # The 'folder_path' is the path to the folder containing the OME-TIF image files and the XML configuration file.
>>> folder_path = OPHYS_DATA_PATH / "imaging_datasets" / "BrukerTif" / "NCCR32_2022_11_03_IntoTheVoid_t_series-005"
>>> converter = BrukerTiffMultiPlaneConverter(folder_path=folder_path, plane_separation_type="contiguous")
>>>
>>> metadata = converter.get_metadata()
>>> # For data provenance we can add the time zone information to the conversion if missing
>>> session_start_time = metadata["NWBFile"]["session_start_time"]
>>> tzinfo = ZoneInfo("US/Pacific")
>>> metadata["NWBFile"].update(session_start_time=session_start_time.replace(tzinfo=tzinfo))
>>>
>>> # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{output_folder}/test2.nwb"
>>> converter.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata)