A Monte Carlo framework for low dose CT reconstruction testing

Jonathan H. Mason; Willam H. Nailon; Mike E. Davies

doi:10.1007/978-3-319-68127-6_9

A Monte Carlo framework for low dose CT reconstruction testing

Jonathan H. Mason^*, Willam H. Nailon, Mike E. Davies

^*Corresponding author for this work

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

We propose a framework using freely available tools for the synthesis of physically realistic CT measurements for low dose reconstruction development and validation, using a fully sampled Monte Carlo method. This allows the generation of test data that has artefacts such as photon starvation, beam-hardening and scatter, that are both physically realistic and not unfairly biased towards model-based iterative reconstruction (MBIR) algorithms. Using the open source Monte Carlo tool GATE and spectrum simulator SpekCalc, we describe how physical elements such as source, specimen and detector may be modelled, and demonstrate the construction of fan-beam and cone-beam CT systems. We then show how this data may be consolidated and used with image reconstruction tools. We give examples with a low dose polyenergetic source, and quantitatively analyse reconstructions against the numerical ground-truth for MBIR with simulated and ‘inverse crime’ data. The proposed framework offers a flexible and easily reproducible tool to aid MBIR development, and may reduce the gap between synthetic and clinical results.

Original language	English
Title of host publication	Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings
Publisher	Springer
Pages	79-88
Number of pages	10
Volume	10557 LNCS
ISBN (Print)	9783319681269
DOIs	https://doi.org/10.1007/978-3-319-68127-6_9
Publication status	Published - 2017
Event	2nd International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 - Quebec City, Canada Duration: 10 Sept 2017 → 10 Sept 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10557 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	2nd International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Country/Territory	Canada
City	Quebec City
Period	10/09/17 → 10/09/17

Keywords / Materials (for Non-textual outputs)

Computed tomography
Iterative reconstruction
Low dose
Simulation
Synthesis

Access to Document

10.1007/978-3-319-68127-6_9

Cite this

Mason, J. H., Nailon, W. H., & Davies, M. E. (2017). A Monte Carlo framework for low dose CT reconstruction testing. In Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings (Vol. 10557 LNCS, pp. 79-88). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10557 LNCS). Springer. https://doi.org/10.1007/978-3-319-68127-6_9

Mason, Jonathan H. ; Nailon, Willam H. ; Davies, Mike E. / A Monte Carlo framework for low dose CT reconstruction testing. Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10557 LNCS Springer, 2017. pp. 79-88 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{01ff9fd2cbee441c92ac9a6aba2c1562,

title = "A Monte Carlo framework for low dose CT reconstruction testing",

abstract = "We propose a framework using freely available tools for the synthesis of physically realistic CT measurements for low dose reconstruction development and validation, using a fully sampled Monte Carlo method. This allows the generation of test data that has artefacts such as photon starvation, beam-hardening and scatter, that are both physically realistic and not unfairly biased towards model-based iterative reconstruction (MBIR) algorithms. Using the open source Monte Carlo tool GATE and spectrum simulator SpekCalc, we describe how physical elements such as source, specimen and detector may be modelled, and demonstrate the construction of fan-beam and cone-beam CT systems. We then show how this data may be consolidated and used with image reconstruction tools. We give examples with a low dose polyenergetic source, and quantitatively analyse reconstructions against the numerical ground-truth for MBIR with simulated and {\textquoteleft}inverse crime{\textquoteright} data. The proposed framework offers a flexible and easily reproducible tool to aid MBIR development, and may reduce the gap between synthetic and clinical results.",

keywords = "Computed tomography, Iterative reconstruction, Low dose, Simulation, Synthesis",

author = "Mason, {Jonathan H.} and Nailon, {Willam H.} and Davies, {Mike E.}",

year = "2017",

doi = "10.1007/978-3-319-68127-6_9",

language = "English",

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volume = "10557 LNCS",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings",

address = "United Kingdom",

note = "2nd International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 ; Conference date: 10-09-2017 Through 10-09-2017",

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Mason, JH, Nailon, WH & Davies, ME 2017, A Monte Carlo framework for low dose CT reconstruction testing. in Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. vol. 10557 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10557 LNCS, Springer, pp. 79-88, 2nd International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, Quebec City, Canada, 10/09/17. https://doi.org/10.1007/978-3-319-68127-6_9

A Monte Carlo framework for low dose CT reconstruction testing. / Mason, Jonathan H.; Nailon, Willam H.; Davies, Mike E.
Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10557 LNCS Springer, 2017. p. 79-88 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10557 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Monte Carlo framework for low dose CT reconstruction testing

AU - Mason, Jonathan H.

AU - Nailon, Willam H.

AU - Davies, Mike E.

PY - 2017

Y1 - 2017

N2 - We propose a framework using freely available tools for the synthesis of physically realistic CT measurements for low dose reconstruction development and validation, using a fully sampled Monte Carlo method. This allows the generation of test data that has artefacts such as photon starvation, beam-hardening and scatter, that are both physically realistic and not unfairly biased towards model-based iterative reconstruction (MBIR) algorithms. Using the open source Monte Carlo tool GATE and spectrum simulator SpekCalc, we describe how physical elements such as source, specimen and detector may be modelled, and demonstrate the construction of fan-beam and cone-beam CT systems. We then show how this data may be consolidated and used with image reconstruction tools. We give examples with a low dose polyenergetic source, and quantitatively analyse reconstructions against the numerical ground-truth for MBIR with simulated and ‘inverse crime’ data. The proposed framework offers a flexible and easily reproducible tool to aid MBIR development, and may reduce the gap between synthetic and clinical results.

AB - We propose a framework using freely available tools for the synthesis of physically realistic CT measurements for low dose reconstruction development and validation, using a fully sampled Monte Carlo method. This allows the generation of test data that has artefacts such as photon starvation, beam-hardening and scatter, that are both physically realistic and not unfairly biased towards model-based iterative reconstruction (MBIR) algorithms. Using the open source Monte Carlo tool GATE and spectrum simulator SpekCalc, we describe how physical elements such as source, specimen and detector may be modelled, and demonstrate the construction of fan-beam and cone-beam CT systems. We then show how this data may be consolidated and used with image reconstruction tools. We give examples with a low dose polyenergetic source, and quantitatively analyse reconstructions against the numerical ground-truth for MBIR with simulated and ‘inverse crime’ data. The proposed framework offers a flexible and easily reproducible tool to aid MBIR development, and may reduce the gap between synthetic and clinical results.

KW - Computed tomography

KW - Iterative reconstruction

KW - Low dose

KW - Simulation

KW - Synthesis

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U2 - 10.1007/978-3-319-68127-6_9

DO - 10.1007/978-3-319-68127-6_9

M3 - Conference contribution

AN - SCOPUS:85031422562

SN - 9783319681269

VL - 10557 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 79

EP - 88

BT - Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings

PB - Springer

T2 - 2nd International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017

Y2 - 10 September 2017 through 10 September 2017

ER -

Mason JH, Nailon WH, Davies ME. A Monte Carlo framework for low dose CT reconstruction testing. In Simulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10557 LNCS. Springer. 2017. p. 79-88. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-68127-6_9

A Monte Carlo framework for low dose CT reconstruction testing

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Keywords / Materials (for Non-textual outputs)

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