Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/87770
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Health Technology and Informatics | en_US |
dc.creator | Harris, W | en_US |
dc.creator | Yin, FF | en_US |
dc.creator | Cai, J | en_US |
dc.creator | Ren, L | en_US |
dc.date.accessioned | 2020-08-19T06:26:54Z | - |
dc.date.available | 2020-08-19T06:26:54Z | - |
dc.identifier.issn | 2223-4292 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/87770 | - |
dc.language.iso | en | en_US |
dc.publisher | AME Publishing Company | en_US |
dc.rights | All AME journals content is published Open Access under the Creative Commons Attribution-NonCommercial-NoDerivs License (CC BY-NC-ND 4.0). All open access articles published will be immediately and permanently free for everyone to read, download, copy, and distribute as defined by the applied license. Free access and usage: Permitted third party reuse is defined by the CC BY-NC-ND 4.0 license. This license allows users to copy and distribute the article, provided: | en_US |
dc.rights | - this is not done for commercial purposes and further does not permit distribution of the Article if it is changed or edited in any way. | en_US |
dc.rights | - the user gives appropriate credit (with a link to the formal publication through the relevant DOI) and provides a link to the license but not in an any way implying that the licensor is endorsing the user or the use of the work. | en_US |
dc.rights | - no derivatives including remix, transform, or build upon the material was allowed for distribution. | en_US |
dc.rights | The full details of the license are available at https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.rights | © Quantitative Imaging in Medicine and Surgery. All rights reserved. | en_US |
dc.rights | The following publication Harris W, Yin FF, Cai J, Ren L. Volumetric cine magnetic resonance imaging (VC-MRI) using motion modeling, free-form deformation and multi-slice undersampled 2D cine MRI reconstructed with spatio-temporal low-rank decomposition. Quant Imaging Med Surg 2020;10(2):432-450. doi: 10.21037/qims.2019.12.10 is available at https://dx.doi.org/10.21037/qims.2019.12.10 | en_US |
dc.subject | Volumetric-cine magnetic resonance imaging (volumetric-cine MRI) | en_US |
dc.subject | Target verification | en_US |
dc.subject | Motion modeling | en_US |
dc.subject | Free-form deformation | en_US |
dc.subject | K-t SLR reconstruction | en_US |
dc.title | Volumetric cine magnetic resonance imaging (VC-MRI) using motion modeling, free-form deformation and multi-slice undersampled 2D cine MRI reconstructed with spatio-temporal low-rank decomposition | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 432 | en_US |
dc.identifier.epage | 450 | en_US |
dc.identifier.volume | 10 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.doi | 10.21037/qims.2019.12.10 | en_US |
dcterms.abstract | Background: The purpose of this study is to improve on-board volumetric cine magnetic resonance imaging (VC-MRI) using multi-slice undersampled tine images reconstructed using spatio-temporal k-space data, patient prior 4D-MRI, motion modeling (MM) and free-form deformation (FD) for real-time 3D target verification of liver and lung radiotherapy. | en_US |
dcterms.abstract | Methods: A previous method was developed to generate on-board VC-MRI by deforming prior MRI images based on a MM and a single for m01-06 =m05-slice on-board 2D-cine image. The two major improvements over the previous method are: (I) FD was introduced to estimate VC-MRI to correct for inaccuracies in the MM; (II) multi-slice undersampled 2D-cine images reconstructed by a k-t SLR reconstruction method were used for FD-based estimation to maintain the temporal resolution while improving the accuracy of VC-MRI. The method was evaluated using XCAT lung simulation and four liver patients' data. | en_US |
dcterms.abstract | Results: For XCAT, VC-MRI estimated using ten undersampled sagittal 2D-Line MRIs resulted in volume percent difference/volume dice coefficient/center-of-mass shift of 9.77%+/- 3.71%/0.95 +/- 0.02/0.75 +/- 0.26 mm among all scenarios based on estimation with MM and FD. Adding FD optimization improved VC-MRI accuracy substantially for scenarios with anatomical changes. For patient data, the mean tumor tracking errors were 0.64 +/- 0.51, 0.62 +/- 0.47 and 0.24 +/- 0.24 mm along the superior-inferior (SI), anterior-posterior (AP) and lateral directions, respectively, across all liver patients. | en_US |
dcterms.abstract | Conclusions: It is feasible to improve VC-MRI accuracy while maintaining high temporal resolution using FD and multi-slice undersampled 2D cinc images for real-time 3D target verification. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Quantitative imaging in medicine and surgery, Feb. 2020, v. 10, no. 2, p. 432-450 | en_US |
dcterms.isPartOf | Quantitative imaging in medicine and surgery | en_US |
dcterms.issued | 2020-02 | - |
dc.identifier.isi | WOS:000516822800011 | - |
dc.identifier.scopus | 2-s2.0-85091094024 | - |
dc.identifier.pmid | 32190569 | - |
dc.identifier.eissn | 2223-4306 | en_US |
dc.description.validate | 202008 bcrc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Harris_Vc-Mri_Free-Form_Deformation.pdf | 2.02 MB | Adobe PDF | View/Open |
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