Literature DB >> 25164978

What is the preferred strength setting of the sinogram-affirmed iterative reconstruction algorithm in abdominal CT imaging?

Andrew D Hardie1, Rachel M Nelson, Robert Egbert, William J Rieter, Sameer V Tipnis.   

Abstract

Our primary objective in this study was to determine the preferred strength setting for the sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in abdominal computed tomography (CT) imaging. Sixteen consecutive clinical CT scans of the abdomen were reconstructed by use of traditional filtered back projection (FBP) and 5 SAFIRE strengths: S1-S5. Six readers of differing experience were asked to rank the images on preference for overall diagnostic quality. The contrast-to-noise ratio was not significantly different between SAFIRE S1 and FBP, but increased with increasing SAFIRE strength. For pooled data, S2 and S3 were preferred equally but both were preferred over all other reconstructions. S5 was the least preferred, with FBP the next least preferred. This represents a marked disparity between the image quality based on quantitative parameters and qualitative preference. Care should be taken to factor in qualitative in addition to quantitative aspects of image quality when one is optimizing iterative reconstruction images.

Mesh:

Year:  2014        PMID: 25164978     DOI: 10.1007/s12194-014-0288-8

Source DB:  PubMed          Journal:  Radiol Phys Technol        ISSN: 1865-0333


  12 in total

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Review 2.  X-ray computed tomography.

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3.  Radiation dose reduction with Sinogram Affirmed Iterative Reconstruction technique for abdominal computed tomography.

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4.  Low-dose chest computed tomography with sinogram-affirmed iterative reconstruction, iterative reconstruction in image space, and filtered back projection: studies on image quality.

Authors:  Hye Jeon Hwang; Joon Beom Seo; Hyun Joo Lee; Sang Min Lee; Eun Young Kim; Sang Young Oh; Ji-Eun Kim
Journal:  J Comput Assist Tomogr       Date:  2013 Jul-Aug       Impact factor: 1.826

5.  Stent evaluation in low-dose coronary CT angiography: effect of different iterative reconstruction settings.

Authors:  Wolfgang Wuest; Matthias S May; Michael Scharf; Christian Layritz; Jasmin Eisentopf; Dieter Ropers; Tobias Pflederer; Michael Uder; Stephan Achenbach; Michael M Lell
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6.  Filtered back projection, adaptive statistical iterative reconstruction, and a model-based iterative reconstruction in abdominal CT: an experimental clinical study.

Authors:  Zsuzsanna Deák; Jochen M Grimm; Marcus Treitl; Lucas L Geyer; Ulrich Linsenmaier; Markus Körner; Maximilian F Reiser; Stefan Wirth
Journal:  Radiology       Date:  2012-11-20       Impact factor: 11.105

7.  Reduced-dose low-voltage chest CT angiography with Sinogram-affirmed iterative reconstruction versus standard-dose filtered back projection.

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Journal:  Radiology       Date:  2013-01-07       Impact factor: 11.105

8.  Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques.

Authors:  Sarabjeet Singh; Mannudeep K Kalra; Jiang Hsieh; Paul E Licato; Synho Do; Homer H Pien; Michael A Blake
Journal:  Radiology       Date:  2010-09-09       Impact factor: 11.105

9.  Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study.

Authors:  Amy K Hara; Robert G Paden; Alvin C Silva; Jennifer L Kujak; Holly J Lawder; William Pavlicek
Journal:  AJR Am J Roentgenol       Date:  2009-09       Impact factor: 3.959

10.  Managing patient dose in multi-detector computed tomography(MDCT). ICRP Publication 102.

Authors:  J Valentin
Journal:  Ann ICRP       Date:  2007
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2.  Application of 80-kVp scan and raw data-based iterative reconstruction for reduced iodine load abdominal-pelvic CT in patients at risk of contrast-induced nephropathy referred for oncological assessment: effects on radiation dose, image quality and renal function.

Authors:  Yasunori Nagayama; Shota Tanoue; Akinori Tsuji; Joji Urata; Mitsuhiro Furusawa; Seitaro Oda; Takeshi Nakaura; Daisuke Utsunomiya; Eri Yoshida; Morikatsu Yoshida; Masafumi Kidoh; Machiko Tateishi; Yasuyuki Yamashita
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3.  Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

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4.  CARE Dose 4D combined with sinogram-affirmed iterative reconstruction improved the image quality and reduced the radiation dose in low dose CT of the small intestine.

Authors:  Lin Wang; Shenchu Gong; Jushun Yang; Jie Zhou; Jing Xiao; Jin-Hua Gu; Hong Yang; Jianfeng Zhu; Bosheng He
Journal:  J Appl Clin Med Phys       Date:  2018-12-03       Impact factor: 2.102

5.  Finding the optimal tube current and iterative reconstruction strength in liver imaging; two needles in one haystack.

Authors:  Bibi Martens; Joris G A Bosschee; Sander M J Van Kuijk; Cécile R L P N Jeukens; Maikel T H Brauer; Joachim E Wildberger; Casper Mihl
Journal:  PLoS One       Date:  2022-04-07       Impact factor: 3.240

6.  Increasing iterative reconstruction strength at low tube voltage in coronary CT angiography protocols using 3D-printed and Catphan® 500 phantoms.

Authors:  Kamarul A Abdullah; Mark F McEntee; Warren M Reed; Peter L Kench
Journal:  J Appl Clin Med Phys       Date:  2020-07-13       Impact factor: 2.102

7.  Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.

Authors:  Shuo Yang; Yifan Bie; Guodong Pang; Xingchao Li; Kun Zhao; Changlei Zhang; Hai Zhong
Journal:  J Xray Sci Technol       Date:  2021       Impact factor: 1.535

  7 in total

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