A Monte Carlo framework for low dose CT reconstruction testing

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 ‘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 languageEnglish
Title of host publicationSimulation and Synthesis in Medical Imaging - 2nd International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Proceedings
PublisherSpringer-Verlag
Pages79-88
Number of pages10
Volume10557 LNCS
ISBN (Print)9783319681269
DOIs
Publication statusPublished - 2017
Event2nd 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 Sep 201710 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10557 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference2nd 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
CountryCanada
CityQuebec City
Period10/09/1710/09/17

Keywords

  • Computed tomography
  • Iterative reconstruction
  • Low dose
  • Simulation
  • Synthesis

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