Volumetric Denoising of XCT Data Using Quantum Computing

Quantum computing is an emerging field of technology that utilizes unique properties such as the superposition principle and quantum entanglement, potentially enabling the development of techniques that are drastically faster or even the only feasible solutions compared to classical approaches. Thu...

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Main Authors: Thomas Lang, Anja Heim, Anastasia Papadaki, Kilian Dremel, Dimitri Prjamkov, Martin Blaimer, Markus Firsching, Stefan Kasperl, Theobald O.J. Fuchs
Format: Article
Language:deu
Published: NDT.net 2025-02-01
Series:e-Journal of Nondestructive Testing
Online Access:https://www.ndt.net/search/docs.php3?id=30732
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author Thomas Lang
Anja Heim
Anastasia Papadaki
Kilian Dremel
Dimitri Prjamkov
Martin Blaimer
Markus Firsching
Stefan Kasperl
Theobald O.J. Fuchs
author_facet Thomas Lang
Anja Heim
Anastasia Papadaki
Kilian Dremel
Dimitri Prjamkov
Martin Blaimer
Markus Firsching
Stefan Kasperl
Theobald O.J. Fuchs
author_sort Thomas Lang
collection DOAJ
description Quantum computing is an emerging field of technology that utilizes unique properties such as the superposition principle and quantum entanglement, potentially enabling the development of techniques that are drastically faster or even the only feasible solutions compared to classical approaches. Thus, it promises enormous gains in several domains, including the processing of n-dimensional images, such as those produced by X-ray computed tomography. However, the latter is subject to physical effects that primarily include artifacts and quantum noise. Noise, in particular, is an unavoidable issue that needs to be addressed when processing X-ray data. Therefore, this work considers the denoising of 3D volumetric data using quantum computing. An adaptation of a mathematical denoising model was transformed to be suitable for quantum implementation, and preliminary experiments demonstrated its functionality with two-dimensional images. Here, we first lift this model to be applicable to 3D images. Next, we provide an implementation in form of quantum circuits and consider issues of a practical implementation occurring specifically in 3D. The final implementation is executed on a real X-ray computed tomography dataset, showing that proper denoising can be performed on quantum devices, yet current technological limitations inhibit the application to large datasets.
format Article
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institution Kabale University
issn 1435-4934
language deu
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series e-Journal of Nondestructive Testing
spelling doaj-art-d754b30b15fb4c119a49559239ecd8ed2025-02-06T10:48:19ZdeuNDT.nete-Journal of Nondestructive Testing1435-49342025-02-0130210.58286/30732Volumetric Denoising of XCT Data Using Quantum ComputingThomas Langhttps://orcid.org/0000-0001-5939-3919Anja HeimAnastasia PapadakiKilian DremelDimitri PrjamkovMartin BlaimerMarkus FirschingStefan Kasperlhttps://orcid.org/0000-0002-8118-7609Theobald O.J. Fuchs Quantum computing is an emerging field of technology that utilizes unique properties such as the superposition principle and quantum entanglement, potentially enabling the development of techniques that are drastically faster or even the only feasible solutions compared to classical approaches. Thus, it promises enormous gains in several domains, including the processing of n-dimensional images, such as those produced by X-ray computed tomography. However, the latter is subject to physical effects that primarily include artifacts and quantum noise. Noise, in particular, is an unavoidable issue that needs to be addressed when processing X-ray data. Therefore, this work considers the denoising of 3D volumetric data using quantum computing. An adaptation of a mathematical denoising model was transformed to be suitable for quantum implementation, and preliminary experiments demonstrated its functionality with two-dimensional images. Here, we first lift this model to be applicable to 3D images. Next, we provide an implementation in form of quantum circuits and consider issues of a practical implementation occurring specifically in 3D. The final implementation is executed on a real X-ray computed tomography dataset, showing that proper denoising can be performed on quantum devices, yet current technological limitations inhibit the application to large datasets. https://www.ndt.net/search/docs.php3?id=30732
spellingShingle Thomas Lang
Anja Heim
Anastasia Papadaki
Kilian Dremel
Dimitri Prjamkov
Martin Blaimer
Markus Firsching
Stefan Kasperl
Theobald O.J. Fuchs
Volumetric Denoising of XCT Data Using Quantum Computing
e-Journal of Nondestructive Testing
title Volumetric Denoising of XCT Data Using Quantum Computing
title_full Volumetric Denoising of XCT Data Using Quantum Computing
title_fullStr Volumetric Denoising of XCT Data Using Quantum Computing
title_full_unstemmed Volumetric Denoising of XCT Data Using Quantum Computing
title_short Volumetric Denoising of XCT Data Using Quantum Computing
title_sort volumetric denoising of xct data using quantum computing
url https://www.ndt.net/search/docs.php3?id=30732
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