Evaluation of image quality for 7 iterative reconstruction algorithms in chest computed tomography imaging : A phantom study
Jensen, Kristin ; Hagemo, Guro ; Tingberg, Anders LU
; Steinfeldt-Reisse, Claudius
; Mynarek, Georg Karl
; Rivero, Rodriguez Jezabel
; Fosse, Erik
and Martinsen, Anne Catrine
(2020)
In Journal of Computer Assisted Tomography
44(5).
p.673-680
- Abstract
Objectives This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm. Methods An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details - large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions - was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated. Results Iterative reconstruction algorithms showed significantly... (More)
Objectives This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm. Methods An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details - large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions - was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated. Results Iterative reconstruction algorithms showed significantly better results when compared with FBP for these criteria (regression coefficients/P values in parentheses): vessels (FIRST: -1.8/0.05, AIDR Enhanced: <-2.3/0.01, Veo: <-0.1/0.03, ADMIRE: <-2.1/0.04), lesions (FIRST: <-2.6/0.01, AIDR Enhanced: <-1.9/0.03, IMR1: <-2.7/0.01, Veo: <-2.4/0.02, ADMIRE: -2.3/0.02), image noise (FIRST: <-3.2/0.004, AIDR Enhanced: <-3.5/0.002, IMR1: <-6.1/0.001, iDose: <-2.3/0.02, Veo: <-3.4/0.002, ADMIRE: <-3.5/0.02), image contrast (FIRST: -2.3/0.01, AIDR Enhanced: -2.5/0.01, IMR1: -3.7/0.001, iDose: -2.1/0.02), and artifacts (FIRST: <-3.8/0.004, AIDR Enhanced: <-2.7/0.02, IMR1: <-2.6/0.02, iDose: -2.1/0.04, Veo: -2.6/0.02). The iDose algorithm was the only IR algorithm that maintained the noise frequencies. Conclusions Iterative reconstruction algorithms performed differently on all evaluated criteria, showing the importance of careful implementation of algorithms for diagnostic purposes.
(Less)
- author
- Jensen, Kristin
; Hagemo, Guro
; Tingberg, Anders
LU
; Steinfeldt-Reisse, Claudius
; Mynarek, Georg Karl
; Rivero, Rodriguez Jezabel
; Fosse, Erik
and Martinsen, Anne Catrine
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- computed tomography, image reconstruction, radiologic phantom, thorax
- in
- Journal of Computer Assisted Tomography
- volume
- 44
- issue
- 5
- pages
- 8 pages
- publisher
- Lippincott Williams & Wilkins
- external identifiers
-
- pmid:32936576
- scopus:85091129214
- ISSN
- 0363-8715
- DOI
- 10.1097/RCT.0000000000001037
- language
- English
- LU publication?
- yes
- id
- 8a47f1f6-8c39-41a8-9de4-c1cc24bfbb52
- date added to LUP
- 2020-10-27 13:22:32
- date last changed
- 2024-10-03 11:17:04
@article{8a47f1f6-8c39-41a8-9de4-c1cc24bfbb52,
abstract = {{<p>Objectives This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm. Methods An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details - large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions - was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated. Results Iterative reconstruction algorithms showed significantly better results when compared with FBP for these criteria (regression coefficients/P values in parentheses): vessels (FIRST: -1.8/0.05, AIDR Enhanced: <-2.3/0.01, Veo: <-0.1/0.03, ADMIRE: <-2.1/0.04), lesions (FIRST: <-2.6/0.01, AIDR Enhanced: <-1.9/0.03, IMR1: <-2.7/0.01, Veo: <-2.4/0.02, ADMIRE: -2.3/0.02), image noise (FIRST: <-3.2/0.004, AIDR Enhanced: <-3.5/0.002, IMR1: <-6.1/0.001, iDose: <-2.3/0.02, Veo: <-3.4/0.002, ADMIRE: <-3.5/0.02), image contrast (FIRST: -2.3/0.01, AIDR Enhanced: -2.5/0.01, IMR1: -3.7/0.001, iDose: -2.1/0.02), and artifacts (FIRST: <-3.8/0.004, AIDR Enhanced: <-2.7/0.02, IMR1: <-2.6/0.02, iDose: -2.1/0.04, Veo: -2.6/0.02). The iDose algorithm was the only IR algorithm that maintained the noise frequencies. Conclusions Iterative reconstruction algorithms performed differently on all evaluated criteria, showing the importance of careful implementation of algorithms for diagnostic purposes. </p>}},
author = {{Jensen, Kristin and Hagemo, Guro and Tingberg, Anders and Steinfeldt-Reisse, Claudius and Mynarek, Georg Karl and Rivero, Rodriguez Jezabel and Fosse, Erik and Martinsen, Anne Catrine}},
issn = {{0363-8715}},
keywords = {{computed tomography; image reconstruction; radiologic phantom; thorax}},
language = {{eng}},
number = {{5}},
pages = {{673--680}},
publisher = {{Lippincott Williams & Wilkins}},
series = {{Journal of Computer Assisted Tomography}},
title = {{Evaluation of image quality for 7 iterative reconstruction algorithms in chest computed tomography imaging : A phantom study}},
url = {{http://dx.doi.org/10.1097/RCT.0000000000001037}},
doi = {{10.1097/RCT.0000000000001037}},
volume = {{44}},
year = {{2020}},
}