A novel morphological-based carotid artery contour extraction

Abdel-Dayem, Amr R.; Ei-Sakka, M.R.

doi:10.1109/ccece.2004.1347574

Cited by 11 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hamou et al [32] proposed a method that was based on the Canny edge detector to detect the plaque regions, prior histogram equalization, in longitudinal 2D CCA ultrasound images. Abdel-Dayen et al [1] used a morphological approach for the carotid contour extraction for longitudinal ultrasound images of the CCA, incorporating speckle reduction filtering, contour quantization, morphological contour detection, and a contour enhancement stage. Abolmaesumi et al [2] introduced an algorithm based on the star algorithm improved by Kalman filtering, for extracting the CCA boundaries from transversal ultrasound images.…”

Section: Atherosclerotic Carotid Plaque Image Segmentation Techniquesmentioning

confidence: 99%

A review of ultrasound common carotid artery image and video segmentation techniques

Loizou

2014

Med Biol Eng Comput

View full text Add to dashboard Cite

The determination of the wall thickness [intima-media thickness (IMT)], the delineation of the atherosclerotic carotid plaque, the measurement of the diameter in the common carotid artery (CCA), as well as the grading of its stenosis are important for the evaluation of the atherosclerosis disease. All these measurements are also considered to be significant markers for the clinical evaluation of the risk of stroke. A number of CCA segmentation techniques have been proposed in the last few years either for the segmentation of the intima-media complex (IMC), the lumen of the CCA, or for the atherosclerotic carotid plaque from ultrasound images or videos of the CCA. The present review study proposes and discusses the methods and systems introduced so far in the literature for performing automated or semi-automated segmentation in ultrasound images or videos of the CCA. These are based on edge detection, active contours, level sets, dynamic programming, local statistics, Hough transform, statistical modeling, neural networks, and an integration of the above methods. Furthermore, the performance of these systems is evaluated and discussed based on various evaluation metrics. We finally propose the best performing method that can be used for the segmentation of the IMC and the atherosclerotic carotid plaque in ultrasound images and videos. We end the present review study with a discussion of the different image and video CCA segmentation techniques, future perspectives, and further extension of these techniques to ultrasound video segmentation and wall tracking of the CCA. Future work on the segmentation of the CCA will be focused on the development of integrated segmentation systems for the complete segmentation of the CCA as well as the segmentation and motion analysis of the plaque and or the IMC from ultrasound video sequences of the CCA. These systems will improve the evaluation, follow up, and treatment of patients affected by advanced atherosclerosis disease conditions.

show abstract

Section: Atherosclerotic Carotid Plaque Image Segmentation Techniquesmentioning

confidence: 99%

A review of ultrasound common carotid artery image and video segmentation techniques

Loizou

2014

Med Biol Eng Comput

View full text Add to dashboard Cite

show abstract

“…Segmentation method 2D/3D AIC N Ultrasound imaging Zahalka et al [5] Deformable models 3D No 69 Hamou et al [6] Canny edge detection 2D No -Abdel-Dayen et al [7] Morphological based 2D No -Mao et al [8] Discrete dynamic contour 2D No 7 Abolmaesumi et al [9] Kalman filtering 2D No 1 Gill et al [10] Balloon 3D No 2 Delsanto et al [11] Deformable parametric model 2D No 45 Loizou et al [12] Snakes 2D Yes 80 Guerrero et al [13] Star-Kalman algorithm 2D No -Golemati et al [14] Hough transforms 2D No 56 Slabaugh et al [15] Region-based active contour 2D No -IVUS imaging Zhang [16] Optimal graph searching 2D No 20 Cardinal [17] Fast-marching method 2D No 200 Brusseau [18] Statistical approach 2D Yes 15 Olszewski [19] Knowledge based 3D No 21 Magnetic resonance imaging (MRI) Xu [20] Mean shift 2D Yes 22 Adams [21] Snakes, GVF 2D No 20 Yang [22] Dynamic programming 2D Yes 62…”

Section: Studymentioning

confidence: 99%

“…Hamou et al [6] proposed a method, which was based on the Canny edge detector to detect the plaque regions in longitudinal carotid artery ultrasound images. A morphological-based approach for the carotid contour extraction was proposed in [7] for longitudinal ultrasound images of carotid artery, incorporating speckle reduction filtering, contour quantization, morphological contour detection, and a contour enhancement stage. Mao et al [8] Table 19.1 An overview of atherosclerotic carotid plaque segmentation techniques…”

Section: Introductionmentioning

confidence: 99%