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Reference TypeConference Paper (Conference Proceedings)
Last Update2013:
Metadata Last Update2020: administrator
Citation KeyAguena:2013:MRItSu
TitleMRI Iterative Super Resolution with Wiener Filter Regularization
Access Date2021, Jan. 27
Number of Files1
Size1628 KiB
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AuthorAguena, Marcia Luciana Silva
AffiliationFederal University of São Carlos
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
DateAug. 5-8, 2013
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2013-07-13 00:46:40 :: -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsSuper-Resolution, Swallowing MRI, Wiener Filter, Conjugate Gradient, Bayesian Regularization.
AbstractThe swallowing process affects several aspects of one's welfare, as nutrition, hydration, respiration and hearing. Magnetic resonance imaging (MRI) has been a valuable tool to study swallowing, since it is a non-invasive procedure that can dynamically capture the shapes of the tongue and other elements involved in the process. The resolution enhancement of the MRI frames support directly diseases diagnoses, helping the visual analysis, or can be a pre-processing tool to segmentation, classification, recognition or modelling. MRI frames with better resolution, with less blurring or noise can be obtained changing the acquisition process, or using more powerful devices, but the cost of this solution is higher than applying computational Super-Resolution (SR) techniques. This paper studies a Bayesian approach to provide a Wiener filter to regularize the conjugate gradient solution, and promote an adaptation of an iterative SR method for non-rigid registration that can be generalized to other iterative SR methods.
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