Literature DB >> 26459319

Image quality in CT: From physical measurements to model observers.

F R Verdun1, D Racine2, J G Ott2, M J Tapiovaara3, P Toroi3, F O Bochud2, W J H Veldkamp4, A Schegerer5, R W Bouwman6, I Hernandez Giron7, N W Marshall8, S Edyvean9.   

Abstract

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.
Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computed tomography; Image quality; Model observer; Patient dose optimisation

Mesh:

Year:  2015        PMID: 26459319     DOI: 10.1016/j.ejmp.2015.08.007

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  41 in total

1.  Signal template generation from acquired images for model observer-based image quality analysis in mammography.

Authors:  Christiana Balta; Ramona W Bouwman; Wouter J H Veldkamp; Mireille J M Broeders; Ioannis Sechopoulos; Ruben E van Engen
Journal:  J Med Imaging (Bellingham)       Date:  2018-09-08

2.  [Quantitative evaluation of image quality of megavoltage computed tomography for guiding helical tomotherapy].

Authors:  Y L Huang; C G Li; K Mao; J A Wu; T T Dai; Y Y Han; H Wu; H Y Wang; Y B Zhang
Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2019-06-18

3.  Effect of radiation dose reduction on texture measures of trabecular bone microstructure: an in vitro study.

Authors:  Muthu Rama Krishnan Mookiah; Thomas Baum; Kai Mei; Felix K Kopp; Georg Kaissis; Peter Foehr; Peter B Noel; Jan S Kirschke; Karupppasamy Subburaj
Journal:  J Bone Miner Metab       Date:  2017-04-07       Impact factor: 2.626

4.  Lack of agreement between radiologists: implications for image-based model observers.

Authors:  Juhun Lee; Robert M Nishikawa; Ingrid Reiser; Margarita L Zuley; John M Boone
Journal:  J Med Imaging (Bellingham)       Date:  2017-05-03

5.  Deep-learning-based model observer for a lung nodule detection task in computed tomography.

Authors:  Hao Gong; Qiyuan Hu; Andrew Walther; Chi Wan Koo; Edwin A Takahashi; David L Levin; Tucker F Johnson; Megan J Hora; Shuai Leng; Joel G Fletcher; Cynthia H McCollough; Lifeng Yu
Journal:  J Med Imaging (Bellingham)       Date:  2020-06-30

6.  Five-star rating system for acceptable quality and dose in CT.

Authors:  Mannudeep K Kalra; Madan M Rehani
Journal:  Eur Radiol       Date:  2021-06-11       Impact factor: 5.315

7.  Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

Authors:  Christopher P Favazza; Andrea Ferrero; Lifeng Yu; Shuai Leng; Kyle L McMillan; Cynthia H McCollough
Journal:  J Med Imaging (Bellingham)       Date:  2017-10-03

8.  General equations for optimal selection of diagnostic image acquisition parameters in clinical X-ray imaging.

Authors:  Xiaoming Zheng
Journal:  Radiol Phys Technol       Date:  2017-08-18

9.  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

10.  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

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