surfcut-python is an incomplete port of the SurfCut macro for ImageJ/FIJI

If you would like to use SurfCut, we recommend the original macro. However, if you want to use this Python version, please do get in touch.

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

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