Literature DB >> 24989382

Objective assessment of image quality and dose reduction in CT iterative reconstruction.

J Y Vaishnav1, W C Jung1, L M Popescu2, R Zeng2, K J Myers2.   

Abstract

PURPOSE: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve.
METHODS: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction.
RESULTS: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance.
CONCLUSIONS: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality.

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Year:  2014        PMID: 24989382     DOI: 10.1118/1.4881148

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  26 in total

1.  DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography.

Authors:  Ehsan Abadi; Brian Harrawood; Shobhit Sharma; Anuj Kapadia; William P Segars; Ehsan Samei
Journal:  IEEE Trans Med Imaging       Date:  2018-12-12       Impact factor: 10.048

2.  A CT Scan Harmonization Technique to Detect Emphysema and Small Airway Diseases.

Authors:  Gonzalo Vegas-Sánchez-Ferrero; Raúl San Estépar José
Journal:  Image Anal Mov Organ Breast Thorac Images (2018)       Date:  2018-09-12

Review 3.  Regularization strategies in statistical image reconstruction of low-dose x-ray CT: A review.

Authors:  Hao Zhang; Jing Wang; Dong Zeng; Xi Tao; Jianhua Ma
Journal:  Med Phys       Date:  2018-09-10       Impact factor: 4.071

4.  A limit on dose reduction possible with CT reconstruction algorithms without prior knowledge of the scan subject.

Authors:  Scott S Hsieh; David A Chesler; Dominik Fleischmann; Norbert J Pelc
Journal:  Med Phys       Date:  2016-03       Impact factor: 4.071

5.  Assessment of structural similarity in CT using filtered backprojection and iterative reconstruction: a phantom study with 3D printed lung vessels.

Authors:  Raoul M S Joemai; Jacob Geleijns
Journal:  Br J Radiol       Date:  2017-08-22       Impact factor: 3.039

6.  Evaluation of low-contrast detectability for iterative reconstruction in pediatric abdominal computed tomography: a phantom study.

Authors:  Nicholas Rubert; Richard Southard; Susan M Hamman; Ryan Robison
Journal:  Pediatr Radiol       Date:  2019-11-09

7.  Rapid measurement of the low contrast detectability of CT scanners.

Authors:  Akinyinka Omigbodun; J Y Vaishnav; Scott S Hsieh
Journal:  Med Phys       Date:  2021-01-13       Impact factor: 4.071

8.  Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

Authors:  Grace J Gang; Jeffrey H Siewerdsen; J Webster Stayman
Journal:  IEEE Trans Med Imaging       Date:  2017-10-16       Impact factor: 10.048

9.  CT of facial fracture fixation: an experimental study of artefact reducing methods.

Authors:  Elina M Peltola; Teemu Mäkelä; Ville Haapamäki; Anni Suomalainen; Junnu Leikola; Seppo K Koskinen; Mika Kortesniemi; Mika P Koivikko
Journal:  Dentomaxillofac Radiol       Date:  2016-10-27       Impact factor: 2.419

10.  Can conclusions drawn from phantom-based image noise assessments be generalized to in vivo studies for the nonlinear model-based iterative reconstruction method?

Authors:  Daniel Gomez-Cardona; Ke Li; Jiang Hsieh; Meghan G Lubner; Perry J Pickhardt; Guang-Hong Chen
Journal:  Med Phys       Date:  2016-02       Impact factor: 4.071

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