Core Imaging Library -- Part II: Multichannel reconstruction for dynamic and spectral tomography

TL;DR

This paper presents the application of the Core Imaging Library (CIL) for multichannel tomographic reconstruction, including dynamic and spectral data, showcasing its flexibility and capabilities through case studies.

Contribution

It introduces formalised optimization problems for multichannel tomography and demonstrates CIL's ability to implement advanced reconstruction algorithms.

Findings

CIL effectively handles multichannel, dynamic, and spectral data.

Case studies show improved reconstruction quality.

CIL provides flexible tools for tailored tomographic algorithms.

Abstract

The newly developed Core Imaging Library (CIL) is a flexible plug and play library for tomographic imaging with a specific focus on iterative reconstruction. CIL provides building blocks for tailored regularised reconstruction algorithms and explicitly supports multichannel tomographic data. In the first part of this two-part publication, we introduced the fundamentals of CIL. This paper focuses on applications of CIL for multichannel data, e.g., dynamic and spectral. We formalise different optimisation problems for colour processing, dynamic and hyperspectral tomography and demonstrate CIL's capabilities for designing state of the art reconstruction methods through case studies and code snapshots.