SEM-FIB-Tomography Mapper is a tool designed for mapping SEM (Scanning Electron Microscope) images and SEM-FIB Tomography metadata to a uniform, schema-compliant json format. This project includes functionality for both SEM and tomography mapping, sharing a common mapping concept.
The target format of the mapper follows pre-defined schemas developed for metadata description of SEM microscopy and SEM-FIB tomography, respectively. Technical information is contained in this repository, for further conceptional description see
- Joseph, R., Chauhan, A., Eschke, C., Ihsan, A. Z., Jalali, M., Jäntsch, U., Jung, N., Shyam Kumar, C. N., Kübel, C., Lucas, C., Mail, M., Mazilkin, A., Neidiger, C., Panighel, M., Sandfeld, S., Stotzka, R., Thelen, R., & Aversa, R. (2021). Metadata schema to support FAIR data in scanning electron microscopy. CEUR-WS.Org. https://doi.org/10.5445/IR/1000141604
- Pauly, C., Joseph, R. E., Vitali, E. G. G., Aversa, R., Stotzka, R., Mücklich, F., Engstler, M., Hermann, H.-G., & Fell, J. (2024). Metadata schema and mapping service for FIB/SEM serial-sectioning and computed tomography. https://doi.org/10.5445/IR/1000175919
Minimal supported python version: 3.10
To get started, clone the repository and navigate to the project directory:
git clone https://github.com/kit-data-manager/tomo_mapper.git
cd tomo_mapper
You can optionally set up a virtual environment. Depending on your environment, you may have to use the python3 alias instead of python for the following commands.
Install the required dependencies:
pip install -r requirements.txt
To run the mapper, use the mapping_cli module:
python -m mapping_cli
1. SEM Mapping
Use the sem subcommand for SEM mapping. The mapper expects a map file, an image or image metadata file, and a JSON output path:
python -m mapping_cli sem -m <map_file> -i <zip_file> -o <json_output_path>
For further information about the necessary map file, see Mapping README
2. Tomography Mapping
Use the tomo subcommand for tomography mapping. The mapper expects a map file, a zip file, and a JSON output path:
python -m mapping_cli tomo -m <map_file> -i <zip_file> -o <json_output_path>
For further information about the necessary map file, see Parsing README
For further information about mappings used internally, see Mapping README
Each release contains the python CLI as platform-specific packaged executable. Usage is identical to use with python, just replace
python -m mapping_cli with the platform-specific executable.
3. Usage as plugin for the Mapping-Service
The mapper can be used as a plugin for the kit-data-manager/Mapping-Service. The necessary gradle project to build the plugin is included in the plugin subfolder.
Plugin and Python code base share the same semantic versioning, so the plugin version always indicates the specific script version used for mapping.
Run tests using pytest:
pytest
Due to the large range and variety of vendors, instruments and setups we cannot guarantee successful mapping for all cases. The following list provides the minimal range of formats, that have been tested via sample data.
- tiff format
- Carl Zeiss SEM (Zeiss instruments, tag 34118)
- FibicsXML (Zeiss instruments, tag 51023)
- FEI Helios (FEI / Thermofisher, tag 34682)
- XML format
- ATLAS3D-Job (Zeiss)
- ATLAS3D-Setup (Zeiss)
- EMProject (Thermofisher)
- ProjectData (Thermofisher)
- Tescan png hdr files
- JEOL bmp hdr files
This work is supported by the consortium NFDI-MatWerk, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 38/1 – project number 460247524.
All sample and test data included in this repository, if not otherwise specified, was contributed by participant projects of NFDI-Matwerk. Special thanks to participant project pp13.