PoCA: Point Cloud Analyst


PoCA is a a powerful stand-alone software designed to ease the manipulation and quantification of multidimensional and multicolor SMLM point cloud data. It is built around a custom-made Open-GL-based rendering engine that provides full user interactive control of SMLM point cloud data, both for visualization and manipulation. It combines the strengths of both C++ and Python programming languages, providing access to efficient and optimized C++ computer graphics algorithms and Python ecosystem. It is designed for improving users and developers’ experience, by integrating a user-friendly GUI, a macro recorder, and the capability to execute Python code easily. PoCA is the result of a decade of developments and the legacy of SR-Tesseler and Coloc-Tesseler, software solutions that were swiftly adopted by the community.

If you use it, please cite it:

PoCA is developed by Florian Levet, researcher in the Quantitative Imaging of the Cell team, headed by Jean-Baptiste Sibarita. FL and JBS are part of the Interdisciplinary Insitute for Neuroscience. FL is part of the Bordeaux Imaging Center.

If you search for support, please open a thread on the image.sc forum or raise an issue here.


Use cases