Surfcut for Python & Matlab is based on Surfcut for ImageJ
Paper: Erguvan, O., Louveaux, M., Hamant, O., Verger, S. (2019) ImageJ SurfCut: a user-friendly pipeline for high-throughput extraction of cell contours from 3D image stacks. BMC Biology, 17:38. https://doi.org/10.1186/s12915-019-0657-1
Software: Verger Stéphane. (2019, April 10). sverger/SurfCut: SurfCut (Version v1.1.0). Zenodo. http://doi.org/10.5281/zenodo.2635737
Example Data: Erguvan Özer, & Verger Stéphane. (2019). Dataset of confocal microscopy stacks from plant samples - ImageJ SurfCut: a user-friendly, high-throughput pipeline for extracting cell contours from 3D confocal stacks [Data set]. Zenodo. http://doi.org/10.5281/zenodo.2577053
Headless Mode
If you are a Python user, this package is available on pip:
pip install surfcut
To run from the command line:
surfcut <image name>.tif
This version implements Surfcut exactly as in the original paper.
A version including morphological operations (erode and dilate) is available for surfaces which are very curved, but is much slower than the original approach.
surfcut <image name>.tif -m
For more options:
surfcut --help
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Release files for surfcut 0.0.3
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| surfcut-0.0.3.tar.gz | 5.0 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| surfcut-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.7 kB
Release files / surfcut-0.0.3.tar.gz
| Download URL | surfcut-0.0.3.tar.gz |
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Release files / surfcut-0.0.3-py3-none-any.whl
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