Publication:
Wavelet-based aortic annulus sizing of echocardiography images

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dc.Conferencecode132915
dc.Conferencedate12 September 2017 through 14 September 2017
dc.Conferencename5th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017
dc.FundingDetailsUniversiti Teknologi Malaysia
dc.FundingDetailsUniversiti Teknologi Malaysia (UTM)
dc.contributor.affiliationsFaculty of Engineering and Built Environment
dc.contributor.affiliationsUniversiti Teknologi Malaysia (UTM)
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorMohammad N.en_US
dc.contributor.authorOmar Z.en_US
dc.contributor.authorSheikh U.U.en_US
dc.contributor.authorRahman A.A.-H.A.en_US
dc.contributor.authorSahrim M.en_US
dc.date.accessioned2024-05-28T08:24:51Z
dc.date.available2024-05-28T08:24:51Z
dc.date.issued2017
dc.description.abstractAortic stenosis (AS) is a condition where the calcification deposit within the heart leaflets narrows the valve and restricts the blood from flowing through it. This disease is progressive over time where it may affect the mechanism of the heart valve. To alleviate this condition without resorting to surgery, which runs the risk of mortality, a new method of treatment has been introduced: Transcatheter Aortic Valve Implantation (TAVI), in which imagery acquired from real-Time echocardiogram (Echo) are needed to determine the exact size of aortic annulus. However, Echo data often suffers from speckle noise and low pixel resolution, which may result in incorrect sizing of the annulus. Our study therefore aims to perform an automated detection and measurement of aortic annulus size from Echo imagery. Two stages of algorithm are presented-image denoising and object detection. For the removal of speckle noise, Wavelet thresholding technique is applied. It consists of three sequential steps; applying linear discrete wavelet transform, thresholding wavelet coefficients and performing linear inverse wavelet transform. For the next stage of analysis, several morphological operations are used to perform object detection as well as valve sizing. The results showed that the automated system is able to produce more accurate sizing based on ground truth. � 2017 IEEE.
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICSIPA.2017.8120586
dc.identifier.epage101
dc.identifier.isbn9781510000000
dc.identifier.scopus2-s2.0-85041408042
dc.identifier.spage96
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85041408042&doi=10.1109%2fICSIPA.2017.8120586&partnerID=40&md5=3a243264ab5b8d32417d505efa1b14ab
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/8573
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017
dc.sourceScopus
dc.subjectannulusen_US
dc.subjectaorticen_US
dc.subjectdenoisingen_US
dc.subjectdetectionen_US
dc.subjectechocardiogramen_US
dc.subjectsizingen_US
dc.subjectstenosisen_US
dc.subjectTAVIen_US
dc.subjectAutomationen_US
dc.subjectBiomineralizationen_US
dc.subjectBlood vesselsen_US
dc.subjectDiscrete wavelet transformsen_US
dc.subjectEchocardiographyen_US
dc.subjectError detectionen_US
dc.subjectImage denoisingen_US
dc.subjectMathematical morphologyen_US
dc.subjectMathematical transformationsen_US
dc.subjectObject detectionen_US
dc.subjectObject recognitionen_US
dc.subjectSpeckleen_US
dc.titleWavelet-based aortic annulus sizing of echocardiography imagesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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