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Hybrid Iterative Reconstruction for Low Radiation Dose Computed Tomography

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Neural Information Processing (ICONIP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11306))

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Abstract

The purpose of this paper is to study the use of hybrid iterative reconstruction (HIR) technique for radiation dose reduction and its effect on low-contrast resolution. This method is designed to create prior information for improving image quality from low dose CT scanners. We compare the performance of lower radiation dose with the HIR and standard dose with the filtered back projection (FBP) using catphan®504 phantom, which is used to measure various image quality parameters. Results show that there are continuous linear reduction of noise and linear increase of CNR with increasing HIR levels compared to FBP for any given scanning protocol. It is possible to provide equivalent diagnostic image quality at low dose. In this paper, we use a quantitative method to evaluate the noise characteristics. Evidence from phantom tests demonstrates that the shape of NPSHIR is shifted continuously to low frequency with increasing HIR levels compared to FBP for any given scanning protocol. Our study confirms that even if there are continuous reduction of noise and increase of CNR with increasing HIR levels, the performance of human observers did not seem to be improved simultaneously because coarser noise could appear. Our finding that the low-frequency components (HIR) are greater than one of FBP (previously believed) may result in the discrepancy between the performance of human observers and that of the ideal low-contrast objects.

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Change history

  • 13 January 2019

    In the originally published version of chapters 21 and 33 the name of the author Jinhua Sheng was incorrectly spelled as “Jinghua Sheng.” It was corrected to “Jinhua Sheng.”

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Author information

Authors and Affiliations

  1. College of Computer Science, Hangzhou Dianzi University, Hangzhou, Zhejiang, China

    Jinhua Sheng, Bin Chen, Bocheng Wang, Qingqiang Liu, Yangjie Ma & Weixiang Liu

  2. Zhejiang University of Media and Communication, Hangzhou, Zhejiang, China

    Bocheng Wang

Authors
  1. Jinhua Sheng
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  2. Bin Chen
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  3. Bocheng Wang
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  4. Qingqiang Liu
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  5. Yangjie Ma
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  6. Weixiang Liu
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Corresponding author

Correspondence to Jinhua Sheng .

Editor information

Editors and Affiliations

  1. The Chinese Academy of Sciences, Beijing, China

    Long Cheng

  2. City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi Sing Leung

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

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Sheng, J., Chen, B., Wang, B., Liu, Q., Ma, Y., Liu, W. (2018). Hybrid Iterative Reconstruction for Low Radiation Dose Computed Tomography. In: Cheng, L., Leung, A., Ozawa, S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science(), vol 11306. Springer, Cham. https://doi.org/10.1007/978-3-030-04224-0_21

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  • DOI: https://doi.org/10.1007/978-3-030-04224-0_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04223-3

  • Online ISBN: 978-3-030-04224-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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