File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)

Conference Paper: Use of novel iterative reconstruction in CT KUB: approach on improving image quality

TitleUse of novel iterative reconstruction in CT KUB: approach on improving image quality
Authors
Issue Date2013
PublisherSpringerOpen.
Citation
The 2013 European Congress of Radiology, Vienna, Austria, 7-11 March 2013. In Insights into Imaging, 2013, v. 4 n. 1 suppl., p. S336 How to Cite?
AbstractPurpose: To compare image quality on computed tomographic (CT) images acquired with filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT KUB examination. Methods and Materials: 20 patients were scanned with standard protocol CT KUB at our institution. Same raw data were reconstructed using FBP, ASIR and MBIR. Objective and subjective image qualities were assessed. Quantitative data such as objective image noise and mean attenuation were analysed by comparing standard deviations, 95% confidence interval and calculating percentage difference. Mean image noise values and attenuation values were compared between different reconstruction algorithms using ANOVA. The interobserver variation and percentage agreement between the two radiologists for each of the assessed subjective image quality and lesion assessment parameters were estimated by using weighted k-statistics. Kruskal-Wallis rank sum test was used to test for equality of median scores among all subjective parameters. Results: Objective image analysis supports significant noise reduction and superior contrast-to-noise ratio with new MBIR technique (p < 0.05). Subjective image parameters were maximally rated for MBIR followed by ASIR then FBP and show statistical significance differences (p < 0.05). Conclusion: MBIR shows superior reduction in noise and improved image quality (both objective and subjective analysis) compared with ASIR and FBP in the context of CT KUB scanning which is inherently a noisy study. At same dose, we have shown that image quality can be improved by applying MBIR in clinical practice, and if available should be utilised.
Persistent Identifierhttp://hdl.handle.net/10722/197932
ISSN
2015 SCImago Journal Rankings: 1.004

 

DC FieldValueLanguage
dc.contributor.authorVardhanabhuti, V-
dc.contributor.authorRoobottom, C-
dc.contributor.authorIlyas, S-
dc.date.accessioned2014-06-13T08:29:46Z-
dc.date.available2014-06-13T08:29:46Z-
dc.date.issued2013-
dc.identifier.citationThe 2013 European Congress of Radiology, Vienna, Austria, 7-11 March 2013. In Insights into Imaging, 2013, v. 4 n. 1 suppl., p. S336-
dc.identifier.issn1869-4101-
dc.identifier.urihttp://hdl.handle.net/10722/197932-
dc.description.abstractPurpose: To compare image quality on computed tomographic (CT) images acquired with filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT KUB examination. Methods and Materials: 20 patients were scanned with standard protocol CT KUB at our institution. Same raw data were reconstructed using FBP, ASIR and MBIR. Objective and subjective image qualities were assessed. Quantitative data such as objective image noise and mean attenuation were analysed by comparing standard deviations, 95% confidence interval and calculating percentage difference. Mean image noise values and attenuation values were compared between different reconstruction algorithms using ANOVA. The interobserver variation and percentage agreement between the two radiologists for each of the assessed subjective image quality and lesion assessment parameters were estimated by using weighted k-statistics. Kruskal-Wallis rank sum test was used to test for equality of median scores among all subjective parameters. Results: Objective image analysis supports significant noise reduction and superior contrast-to-noise ratio with new MBIR technique (p < 0.05). Subjective image parameters were maximally rated for MBIR followed by ASIR then FBP and show statistical significance differences (p < 0.05). Conclusion: MBIR shows superior reduction in noise and improved image quality (both objective and subjective analysis) compared with ASIR and FBP in the context of CT KUB scanning which is inherently a noisy study. At same dose, we have shown that image quality can be improved by applying MBIR in clinical practice, and if available should be utilised.-
dc.languageeng-
dc.publisherSpringerOpen.-
dc.relation.ispartofInsights into Imaging-
dc.titleUse of novel iterative reconstruction in CT KUB: approach on improving image qualityen_US
dc.typeConference_Paperen_US
dc.identifier.emailVardhanabhuti, V: varv@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s13244-013-0228-x-
dc.identifier.volume4-
dc.identifier.issue1 suppl.-
dc.identifier.spageS336-
dc.identifier.epageS336-
dc.publisher.placeGermany-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats