Literature DB >> 24681863

Initial performance evaluation of iterative model reconstruction in abdominal computed tomography.

Shigeru Suzuki1, Takahiro Haruyama, Hisashi Morita, Yuzuru Takahashi, Reiko Matsumoto.   

Abstract

OBJECTIVE: The aim of this study was to present initial evaluation of the performance of the iterative model reconstruction algorithm (IMR) in abdominal computed tomography (CT).
METHODS: Computed tomographic examinations were performed for clinical study of 36 patients and for phantom study. We reconstructed the raw data with 1.0- and 5.0-mm slice thicknesses using filtered back projection (FBP), iDose4, and IMR and evaluated image quality objectively and subjectively.
RESULTS: For almost all subjective characteristics, the image quality was better using IMR than iDose4. Objective image noise was significantly less using IMR than iDose4 (P < 0.0001). The contrast-noise ratio of both slice thicknesses increased in order from FBP to iDose4 to IMR. The spatial resolution of reconstructed images was almost identical using IMR, FBP, and iDose4.
CONCLUSIONS: The IMR can significantly improve image noise and low-contrast resolution and maintain edge sharpness in abdominal CT images compared with iDose4 or FBP.

Entities:  

Mesh:

Year:  2014        PMID: 24681863     DOI: 10.1097/RCT.0000000000000062

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  9 in total

1.  Feasibility study of low tube voltage (80 kVp) coronary CT angiography combined with contrast medium reduction using iterative model reconstruction (IMR) on standard BMI patients.

Authors:  Fan Zhang; Li Yang; Xiang Song; Ying-Na Li; Yan Jiang; Xing-Hua Zhang; Hai-Yue Ju; Jian Wu; Rui-Ping Chang
Journal:  Br J Radiol       Date:  2015-11-26       Impact factor: 3.039

2.  Image Quality Required for the Diagnosis of Skull Fractures Using Head CT: A Comparison of Conventional and Improved Reconstruction Kernels.

Authors:  S Takagi; M Koyama; K Hayashi; T Kawauchi
Journal:  AJNR Am J Neuroradiol       Date:  2016-07-14       Impact factor: 3.825

3.  Effect of the forward-projected model-based iterative reconstruction solution algorithm on image quality and radiation dose in pediatric cardiac computed tomography.

Authors:  Yukako Nishiyama; Keiji Tada; Yuichi Nishiyama; Hiroshi Mori; Mitsunari Maruyama; Takashi Katsube; Nobuko Yamamoto; Hidekazu Kanayama; Yasushi Yamamoto; Hajime Kitagaki
Journal:  Pediatr Radiol       Date:  2016-08-16

4.  Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.

Authors:  Atsushi Nakamoto; Yoshikazu Tanaka; Hiroshi Juri; Go Nakai; Shushi Yoshikawa; Yoshifumi Narumi
Journal:  Eur Radiol       Date:  2016-12-12       Impact factor: 5.315

5.  Impact of hybrid iterative reconstruction on unenhanced liver CT.

Authors:  Masatoshi Kondo; Akihiro Nishie; Nobuhiro Fujita; Koichiro Morita; Takashi Shirasaka; Hisao Arimura; Yasuhiko Nakamura; Hiroshi Honda
Journal:  Br J Radiol       Date:  2016-12-20       Impact factor: 3.039

6.  Prevalence of extracardiac findings in patients undergoing coronary computed tomography and additional low-dose whole-body computed tomography.

Authors:  Morikatsu Yoshida; Daisuke Utsunomiya; Taihei Inoue; Takeshi Nakaura; Naritsugu Sakaino; Kazunori Harada; Daisuke Sueta; Kenichi Tsujita; Yasuyuki Yamashita
Journal:  Jpn J Radiol       Date:  2019-12-20       Impact factor: 2.374

7.  Improved image quality of low-dose CT combining with iterative model reconstruction algorithm for response assessment in patients after treatment of malignant tumor.

Authors:  Xiaoyan Xin; Jingtao Shen; Shangwen Yang; Song Liu; Anning Hu; Bin Zhu; Yan Jiang; Baoxin Li; Bing Zhang
Journal:  Quant Imaging Med Surg       Date:  2018-08

8.  Comparison of image quality from filtered back projection, statistical iterative reconstruction, and model-based iterative reconstruction algorithms in abdominal computed tomography.

Authors:  Yu Kuo; Yi-Yang Lin; Rheun-Chuan Lee; Chung-Jung Lin; Yi-You Chiou; Wan-Yuo Guo
Journal:  Medicine (Baltimore)       Date:  2016-08       Impact factor: 1.889

9.  Thin-slice brain CT with iterative model reconstruction algorithm for small lacunar lesions detection: Image quality and diagnostic accuracy evaluation.

Authors:  Xiaoyi Liu; Lei Chen; Weiwei Qi; Yan Jiang; Ying Liu; Miao Zhang; Nan Hong
Journal:  Medicine (Baltimore)       Date:  2017-12       Impact factor: 1.817

  9 in total

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