Performance evaluation of computed tomography systems: summary of AAPM Task Group 233

E Samei, D Bakalyar, KL Boedeker, S Brady… - Medical …, 2019 - Wiley Online Library
Background The rapid development and complexity of new x‐ray computed tomography
(CT) technologies and the need for evidence‐based optimization of image quality with …

Virtual clinical trials in medical imaging: a review

E Abadi, WP Segars, BMW Tsui… - Journal of Medical …, 2020 - spiedigitallibrary.org
The accelerating complexity and variety of medical imaging devices and methods have
outpaced the ability to evaluate and optimize their design and clinical use. This is a …

Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study

J Greffier, A Hamard, F Pereira, C Barrau, H Pasquier… - European …, 2020 - Springer
Objectives To assess the impact on image quality and dose reduction of a new deep
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …

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

J Greffier, J Frandon, A Larbi, JP Beregi, F Pereira - European radiology, 2020 - Springer
Purpose To assess the dose performance in terms of image quality of filtered back projection
(FBP) and two generations of iterative reconstruction (IR) algorithms developed by the most …

Assessment of the dose reduction potential of a model‐based iterative reconstruction algorithm using a task‐based performance metrology

E Samei, S Richard - Medical physics, 2015 - Wiley Online Library
Purpose: Different computed tomography (CT) reconstruction techniques offer different
image quality attributes of resolution and noise, challenging the ability to compare their dose …

Assessing the impact of deep neural network-based image denoising on binary signal detection tasks

K Li, W Zhou, H Li, MA Anastasio - IEEE transactions on …, 2021 - ieeexplore.ieee.org
A variety of deep neural network (DNN)-based image denoising methods have been
proposed for use with medical images. Traditional measures of image quality (IQ) have been …

Low-dose abdominal CT using a deep learning-based denoising algorithm: a comparison with CT reconstructed with filtered back projection or iterative reconstruction …

YJ Shin, W Chang, JC Ye, E Kang… - Korean journal of …, 2020 - synapse.koreamed.org
Objective To compare the image quality of low-dose (LD) computed tomography (CT)
obtained using a deep learning-based denoising algorithm (DLA) with LD CT images …

Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods

B Chen, O Christianson, JM Wilson, E Samei - Medical physics, 2014 - Wiley Online Library
Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT)
noise and resolution properties can depend on the specific imaging conditions, such as …

Characteristic image quality of a third generation dual‐source MDCT scanner: noise, resolution, and detectability

J Solomon, J Wilson, E Samei - Medical physics, 2015 - Wiley Online Library
Purpose: The purpose of this work was to assess the inherent image quality characteristics
of a new multidetector computed tomography system in terms of noise, resolution, and …

Radiation dose reduction for 80-kVp pediatric CT using deep learning–based reconstruction: a clinical and phantom study

Y Nagayama, M Goto, D Sakabe… - American Journal of …, 2022 - Am Roentgen Ray Soc
Please see the Editorial Comment by Aaron D. Hodes discussing this article.
BACKGROUND. Deep learning–based reconstruction (DLR) may facilitate CT radiation …