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

Evangelos Papoutsellis, Evelina Ametova, Claire Delplancke, Gemma Fardell, Jakob Sauer Jørgensen, Edoardo Pasca, Martin Turner, Ryan Warr, William Lionheart, Philip J. Withers

2021Repository KITopen (Karlsruhe Institute of Technology)34 citationsDOIOpen Access PDF

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 regularized 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 formalize different optimization 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.

Topics & Concepts

Tomographic reconstructionComputer scienceIterative reconstructionTomographyFocus (optics)Hyperspectral imagingComputer visionCode (set theory)Artificial intelligenceOpticsPhysicsSet (abstract data type)Programming languageMedical Imaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsPhotoacoustic and Ultrasonic Imaging
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