Moubark, AM, Cowell, DMJ orcid.org/0000-0003-0854-542X, Harput, S et al. (1 more author) (2019) New Denoising Unsharp Masking Method for Improved Intima Media Thickness Measurements with Active Contour Segmentation. In: Proceedings of the 2018 IEEE International Ultrasonics Symposium (IUS). 2018 IEEE International Ultrasonics Symposium (IUS), 22-25 Oct 2018, Kobe, Japan. ISBN 978-1-5386-3426-4
Abstract
The semi-automated balloon snake active contour (BSAC) based segmentations play a vital role in determining the intima-media thickness (IMT) for accessing the risk related to cardio vascular diseases (CVD). However, the speckle and clutter noise in the ultrasound B-mode images are known to interfere with the contour formation during segmentation. Both noise sources act as false external energy in BSAC and thus influence the resulting boundary definition. A large number of iterations are required for the BSAC to accurately detect the boundary and in the presence of high noise the segmentation algorithm can result in false detections. Thus in this work we have applied the new denoising unsharp masking (UM) method on human common carotid artery in order to reduce clutter noise in the B-mode image before the segmentation process takes place for faster and accurate IMT measurement. The resuts show the number of iterations needed for BSAC to settle on the final intima-media border is less with UM-DAS (100 iterations) compared to that without the denoising technique, DAS (200 iterations). Thus the proposed UM techniques is able to provide better results with less time in measuring the IMT compared to that using DAS.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Clutter; Image segmentation; Ultrasonic imaging; Carotid arteries; Noise reduction; Imaging; Manuals |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Feb 2020 14:23 |
Last Modified: | 05 Feb 2020 14:46 |
Status: | Published |
Identification Number: | 10.1109/ULTSYM.2018.8579733 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156529 |