Ghita, Dana Ilea, Duffy, Caoimhe, Kavanagh, Liam, Stanton, Alice and Whelan, Paul F. ORCID: 0000-0001-9230-7656 (2013) Fully automated segmentation and tracking of the intima media thickness in ultrasound video sequences of the common carotid artery. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 60 (1). pp. 158-177. ISSN 0885-3010
Abstract
Abstract—The robust identification and measurement of the intima media thickness (IMT) has a high clinical relevance because it represents one of the most precise predictors used in the assessment of potential future cardiovascular events. To facilitate the analysis of arterial wall thickening in serial clinical investigations, in this paper we have developed a novel fully automatic algorithm for the segmentation, measurement, and tracking of the intima media complex (IMC) in B-mode ultrasound video sequences. The proposed algorithm entails a two-stage image analysis process that initially addresses the segmentation of the IMC in the first frame of the ultrasound video sequence using a model-based approach; in the second step, a novel customized tracking procedure is applied to robustly detect the IMC in the subsequent frames. For the video tracking procedure, we introduce a spatially coherent algorithm called adaptive normalized correlation that prevents the tracking process from converging to wrong arterial interfaces. This represents the main contribution of this paper and was developed to deal with inconsistencies in the appearance of the IMC over the cardiac cycle. The quantitative evaluation has been carried out on 40 ultrasound video sequences of the common carotid artery (CCA) by comparing the results returned by the developed algorithm with respect to ground truth data that has been manually annotated by clinical experts. The measured IMTmean ± standard deviation recorded by the proposed algorithm is 0.60 mm ± 0.10, with a mean coefficient of variation (CV) of 2.05%, whereas the corresponding result obtained for the manually annotated ground truth data is 0.60 mm ± 0.11 with a mean CV equal to 5.60%. The numerical results reported in this paper indicate that the proposed algorithm is able to correctly segment and track the IMC in ultrasound CCA video sequences, and we were encouraged by the stability of our technique when applied to data captured under different imaging conditions. Future clinical studies will focus on the evaluation of patients that are affected by advanced cardiovascular conditions such as focal thickening and arterial plaques.
Metadata
Item Type: | Article (Published) |
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Refereed: | Yes |
Uncontrolled Keywords: | cardiovascular events; arterial wall thickening; intima media complex; Analysis |
Subjects: | Computer Science > Computer engineering Computer Science > Image processing |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering |
Publisher: | Institute of Electrical and Electronics Engineers |
Official URL: | http://dx.doi.org/10.1109/TUFFC.2013.2547 |
Copyright Information: | © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 18479 |
Deposited On: | 20 Jun 2013 10:41 by Mark Sweeney . Last Modified 11 Jan 2019 13:15 |
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