Vis within Image Reconstruction

Within our Tomographic Imaging network ccpi.ac.uk we gave a talk Introducing the CCPi Core Imaging Library – Dr Edoardo Pasca (25 January 2022 11am), STFC’s Scientific Computing Department.

Abstract: The Collaborative Computational Project in Tomographic Imaging (CCPi) Core Imaging Library (CIL) is a versatile Python package for tomographic imaging intended for CT experimentalists to easily access optimised standard algorithms, create bespoke pipelines to handle novel imaging rigs, dynamic, hyperspectral, non standard scan geometry, to name a few. CIL is also intended for imaging specialists to allow the creation of novel reconstruction algorithms and assess them against established ones. CIL seamlessly handles the CT pipeline from loading data from common lab X-Ray CT machines, as NIKON or ZEISS, to FDK or iterative reconstruction. CIL also provides utilities for visualisation and exploration of the data. In this seminar, Dr Edoardo Pasca will talk about some examples of applications of the methods available with CIL.

This included a live demonstration – see below – where Edo created a reconstruction of a walnut, X-ray CT scan, where the data (middle image) was severely limited, but modern iterative solutions (right image) achieve almost the same as the gold standard result (left image).

Recording available soon – but one extra almost essential part is an automated visualisation module (also written in python) to describe the lab set up (the geometry of image capture and object space – credit to Gemma Fardell).

So to understand the visualisation of the resulting images; you need to understand the visualisation of the geometry of the laboratory setup.