Literature DB >> 26924832

Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study.

Marie-Louise Aurumskjöld1, Kristina Ydström2, Anders Tingberg2, Marcus Söderberg2.   

Abstract

BACKGROUND: The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose.
PURPOSE: To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction.
MATERIAL AND METHODS: An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose4) and model-based (IMR) iterative reconstruction methods.
RESULTS: iDose4 decreased the noise by 15-45% compared with FBP depending on the level of iDose4. The IMR reduced the noise even further, by 60-75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose4, and the improvement was even greater with IMR.
CONCLUSION: There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality. © The Foundation Acta Radiologica 2016.

Entities:  

Keywords:  Computed tomography (CT); dose reduction; image quality; iterative reconstruction; noise

Mesh:

Year:  2016        PMID: 26924832     DOI: 10.1177/0284185116631180

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  5 in total

1.  Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages.

Authors:  André Euler; Bram Stieltjes; Zsolt Szucs-Farkas; Reto Eichenberger; Clemens Reisinger; Anna Hirschmann; Caroline Zaehringer; Achim Kircher; Matthias Streif; Sabine Bucher; David Buergler; Luigia D'Errico; Sebastién Kopp; Markus Wilhelm; Sebastian T Schindera
Journal:  Eur Radiol       Date:  2017-04-03       Impact factor: 5.315

2.  CT iterative reconstruction algorithms: a task-based image quality assessment.

Authors:  J Greffier; J Frandon; A Larbi; J P Beregi; F Pereira
Journal:  Eur Radiol       Date:  2019-07-29       Impact factor: 5.315

3.  Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study.

Authors:  Kazuya Minamishima; Koichi Sugisawa; Yoshitake Yamada; Masahiro Jinzaki
Journal:  J Appl Clin Med Phys       Date:  2018-02-28       Impact factor: 2.102

4.  Development of an organ-specific insert phantom generated using a 3D printer for investigations of cardiac computed tomography protocols.

Authors:  Kamarul A Abdullah; Mark F McEntee; Warren Reed; Peter L Kench
Journal:  J Med Radiat Sci       Date:  2018-04-30

5.  Evaluation of an integrated 3D-printed phantom for coronary CT angiography using iterative reconstruction algorithm.

Authors:  Kamarul A Abdullah; Mark F McEntee; Warren Reed; Peter L Kench
Journal:  J Med Radiat Sci       Date:  2020-03-27
  5 in total

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