MODEL-BASED ITERATIVE RECONSTRUCTION ENABLES THE EVALUATION OF THIN-SLICE COMPUTED TOMOGRAPHY IMAGES WITHOUT DEGRADING IMAGE QUALITY OR INCREASING RADIATION DOSE.
(2016) In Radiation Protection Dosimetry 169(1-4). p.100-106- Abstract
- Computed tomography (CT) is one of the most important modalities in a radiological department. This technique not only produces images that enable radiological reports with high diagnostic confidence, but it may also provide an elevated radiation dose to the patient. The radiation dose can be reduced by using advanced image reconstruction algorithms. This study was performed on a Brilliance iCT, equipped with iDose(4) iterative reconstruction and an iterative model-based reconstruction (IMR) method. The purpose was to investigate the effect of reduced slice thickness combined with an IMR method on image quality compared with standard slice thickness with iDose(4) reconstruction. The results of objective and subjective image quality... (More)
- Computed tomography (CT) is one of the most important modalities in a radiological department. This technique not only produces images that enable radiological reports with high diagnostic confidence, but it may also provide an elevated radiation dose to the patient. The radiation dose can be reduced by using advanced image reconstruction algorithms. This study was performed on a Brilliance iCT, equipped with iDose(4) iterative reconstruction and an iterative model-based reconstruction (IMR) method. The purpose was to investigate the effect of reduced slice thickness combined with an IMR method on image quality compared with standard slice thickness with iDose(4) reconstruction. The results of objective and subjective image quality evaluations showed that a thinner slice combined with IMR can improve the image quality and reduce partial volume artefacts compared with the standard slice thickness with iDose(4). In conclusion, IMR enables reduction of the slice thickness while maintaining or even improving image quality versus iDose(4). (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8234957
- author
- Aurumskjöld, Marie-Louise LU ; Ydström, Kristina ; Tingberg, Anders LU and Söderberg, Marcus LU
- organization
- publishing date
- 2016-06
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Radiation Protection Dosimetry
- volume
- 169
- issue
- 1-4
- pages
- 100 - 106
- publisher
- Oxford University Press
- external identifiers
-
- pmid:26590394
- pmid:26590394
- scopus:84979085662
- wos:000383492100016
- ISSN
- 1742-3406
- DOI
- 10.1093/rpd/ncv474
- project
- Studies of iterative reconstruction in CT
- language
- English
- LU publication?
- yes
- id
- c21f6689-6934-4c0b-8c77-17f94d2391f0 (old id 8234957)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/26590394?dopt=Abstract
- date added to LUP
- 2016-04-04 09:32:59
- date last changed
- 2024-02-11 12:25:01
@article{c21f6689-6934-4c0b-8c77-17f94d2391f0, abstract = {{Computed tomography (CT) is one of the most important modalities in a radiological department. This technique not only produces images that enable radiological reports with high diagnostic confidence, but it may also provide an elevated radiation dose to the patient. The radiation dose can be reduced by using advanced image reconstruction algorithms. This study was performed on a Brilliance iCT, equipped with iDose(4) iterative reconstruction and an iterative model-based reconstruction (IMR) method. The purpose was to investigate the effect of reduced slice thickness combined with an IMR method on image quality compared with standard slice thickness with iDose(4) reconstruction. The results of objective and subjective image quality evaluations showed that a thinner slice combined with IMR can improve the image quality and reduce partial volume artefacts compared with the standard slice thickness with iDose(4). In conclusion, IMR enables reduction of the slice thickness while maintaining or even improving image quality versus iDose(4).}}, author = {{Aurumskjöld, Marie-Louise and Ydström, Kristina and Tingberg, Anders and Söderberg, Marcus}}, issn = {{1742-3406}}, language = {{eng}}, number = {{1-4}}, pages = {{100--106}}, publisher = {{Oxford University Press}}, series = {{Radiation Protection Dosimetry}}, title = {{MODEL-BASED ITERATIVE RECONSTRUCTION ENABLES THE EVALUATION OF THIN-SLICE COMPUTED TOMOGRAPHY IMAGES WITHOUT DEGRADING IMAGE QUALITY OR INCREASING RADIATION DOSE.}}, url = {{https://lup.lub.lu.se/search/files/8065155/5353935.pdf}}, doi = {{10.1093/rpd/ncv474}}, volume = {{169}}, year = {{2016}}, }