Wavelet-based aortic annulus sizing of echocardiography images

Norhasmira, Mohammad and Zaid, Omar and Usman Ullah, Sheikh and Ab Al-Hadi, Ab Rahman and Mus’ab, Sahrim (2017) Wavelet-based aortic annulus sizing of echocardiography images. In: 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 12-14 September 2017, Kuching, Malaysia.

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Official URL: https://ieeexplore.ieee.org/document/8120586

Abstract

Aortic 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.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: aortic; stenosis; TAVI; annulus; sizing; echocardiogram; denoising; detection.
Subjects: Q Science > QA Mathematics > QA76 Computer software
R Medicine > R Medicine (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Faculties, Institutes, Centres > Faculty of Cognitive Sciences and Human Development
Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Mohammad
Date Deposited: 12 Sep 2024 08:05
Last Modified: 12 Sep 2024 08:05
URI: http://ir.unimas.my/id/eprint/46024

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