Publication:
Wavelet-based Aortic Annulus Sizing of Echocardiography Images

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dc.ConferencecodeIEEE, SARAWAK Convent Bur, IEEE Signal Proc Soc Malaysia Chapter
dc.ConferencedateSEP 12-14, 2017
dc.ConferencelocationKuching, MALAYSIA
dc.ConferencenameIEEE International Conference on Signal and Image Processing Applications (ICSIPA)
dc.contributor.authorMohammad, Nen_US
dc.contributor.authorOmar, Zen_US
dc.contributor.authorSheikh, UUen_US
dc.contributor.authorAb Rahman, Aen_US
dc.contributor.authorSahrim, Men_US
dc.date.accessioned2024-05-29T03:26:41Z
dc.date.available2024-05-29T03:26:41Z
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.
dc.identifier.epage101
dc.identifier.issn2373-681X
dc.identifier.scopusWOS:000427602600018
dc.identifier.spage96
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/12143
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartof2017 Ieee International Conference On Signal And Image Processing Applications (Icsipa)
dc.sourceWeb Of Science (ISI)
dc.subjectaorticen_US
dc.subjectstenosisen_US
dc.subjectTAVIen_US
dc.subjectannulusen_US
dc.subjectsizingen_US
dc.subjectechocardiogramen_US
dc.subjectdenoisingen_US
dc.subjectdetectionen_US
dc.titleWavelet-based Aortic Annulus Sizing of Echocardiography Imagesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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