Computed Tomography

CASToR is an open-source multi-platform project for 4D emission (PET and SPECT) and transmission (CT) tomographic reconstruction. This platform is a scalable software providing both basic image reconstruction features for "standard" users and advance

This is a tool to segment microstructural evolution from 4D tomography data (or other image data).The method is based on clustering of a 2D histogram built from the intensities in a reference state and in an evolved state.

This is a primitive python script designed to enable MARS beamline users to try initial analysis onto tomography volume from X-ray µCT. It relies on manuel segmentation of grey shade value related to the X-ray absorption. The project aims to prototype analysis tools thought and developed in collaboration with the users during the beamtime. The seed project is a set of function managing the volume opening, save/load of work, manual segmentation. It hope that will grow into a great tree, with new branch like, 3D rendering visualisation, data analysis visualisation, labelling, and much more ...

This is a python script open source and free used It follows the iterative correction for limited angle tomography that is describe in the article : https://doi.org/10.1016/j.tmater.2023.100008 If you use it in your data treatment, please quote the article. Stay aware about the use of skimage.radon and iradon which are very slow and not optimised for heavy volume. This is part of the project MushroomSamba

Series of simulations to replicate laboratory experiments as part of a 'digital twin' initiative between Swansea University and the UK Atomic Energy Authority. Scripts are mostly in python to run the various modules which this platform integrates together (e.g., Salome, Code_Aster, ERMES, CAD2Vox, gvxr, CIL).

Homodyne Computed Tomography in Julia

Julia package for CT images reconstruction and analysis

Experimental module for performing a digital tomographic scan of an imported image and then reconstructing it using various techniques.