PATATO: PhotoAcoustic Tomography Analysis TOolkit#
PATATO is an open-source project to enable the analysis of photoacoustic (PA) imaging data in a transparent, reproducible and extendable way. We provide efficient, GPU-optimised implementations of common PA algorithms written around standard Python libraries, including filtered backprojection, model-based reconstruction and spectral unmixing.
The project supports many file formats, such as the International Photoacoustic Standardisation Consortium (IPASC) data format, and it can be extended to support custom data formats. At present, the project contains functions to handle data generated by commercial PA systems by iThera Medical GmbH. The examples will thus be drawn from applications and geometries suitable for those systems. The data used in the examples is freely available online. By providing PATATO as an open-source project, we encourage others to contribute their own algorithms that handle both alternative commercial PA systems and custom home-built systems.
Our goal in providing this toolkit is to provide a framework than can enable faster and wider dissemination of state-of-the-art analysis methods for PA imaging and thus be a useful tool for the community as we translate photoacoustics to the clinic.
Please report any bugs or issues you find to our GitHub repository
Please do get involved! Contact Thomas Else (thomas.else@cruk.cam.ac.uk).
The logo was designed by Elly Pugh.
User Guide
Examples
Developers