Core Imaging Library (CIL)

The Core Imaging Library (CIL) is a set of modules for each process involved in the data analysis workflow of the CT datasets. Starting from the preparing the dataset for reconstruction which involves applying filters to remove the noise and beam hardening to correct the datasets etc to quantifying the segmented volume. The motivation for creating this library is to provide the CT imaging community with set of tools that is easily accessible and that can be integrated into existing workflows such as SAVU. The algorithms are contributed by the community and the core CCPi staff have reengineered the code to make them run faster, easily accessible and maintainable.

CIL consists of a number of algorithms for pre processing, reconstruction, data analysis and visualisation, as depicted in figure below. CIL aims at giving such algorithms a unified way of use, distribution and documentation, though they have been written by different authors, institutions and with different tools.

Thus, CIL provides basic converters to read in data from different scanners and different origins, currently NeXuS format and Nikon.

In the current release, each module is independent from each other, i.e. there is no dependency between the inputs and outputs of the modules. Developers can use these modules independently to analyse their data.

Module Software Repository Version
Pre-Processing
Beam Hardening https://github.com/vais-ral/CCPi-preprocessing
Reconstruction
Framework https://github.com/vais-ral/CCPi-Framework
FrameworkPlugins https://github.com/vais-ral/CCPi-FrameworkPlugins
Astra Plugins https://github.com/vais-ral/CCPi-Astra
Reconstruction https://github.com/vais-ral/CCPi-Reconstruction
Regularisation Toolkit https://github.com/vais-ral/CCPi-Regularisation-Toolkit
TomoPhantom https://github.com/dkazanc/TomoPhantom
Data Analysis
Quantification https://github.com/vais-ral/CCPi-Quantification
Visualisation
Viewer https://github.com/vais-ral/CILViewer

Citation to CIL is the URL http://www.ccpi.ac.uk/CIL