Snakes based segmentation of the common carotid artery intima media

Ultrasound measurements of the human carotid artery walls are conventionally obtained by manually tracing interfaces between tissue layers. In this study we present a snakes segmentation technique for detecting the intima-media layer of the far wall of the common carotid artery (CCA) in longitudinal ultrasound images, by applying snakes, after normalization, speckle reduction, and normalization and speckle reduction. The proposed technique utilizes an improved snake initialization method, and an improved validation of the segmentation method. We have tested and clinically validated the segmentation technique on 100 longitudinal ultrasound images of the carotid artery based on manual measurements by two vascular experts, and a set of different evaluation criteria based on statistical measures and univariate statistical analysis. The results showed that there was no significant difference between all the snakes segmentation measurements and the manual measurements. For the normalized despeckled images, better snakes segmentation results with an intra-observer error of 0.08, a coefficient of variation of 12.5%, best Bland–Altman plot with smaller differences between experts (0.01, 0.09 for Expert1 and Expert 2, respectively), and a Hausdorff distance of 5.2, were obtained. Therefore, the pre-processing of ultrasound images of the carotid artery with normalization and speckle reduction, followed by the snakes segmentation algorithm can be used successfully in the measurement of IMT complementing the manual measurements. The present results are an expansion of data published earlier as an extended abstract in IFMBE Proceedings (Loizou et al. IEEE Int X Mediterr Conf Medicon Med Biol Eng POS-03 499:1–4, 2004).

[1]  Yongmin Kim,et al.  A methodology for evaluation of boundary detection algorithms on medical images , 1997, IEEE Transactions on Medical Imaging.

[2]  Yasser M. Kadah,et al.  Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion , 2002, IEEE Transactions on Biomedical Engineering.

[3]  H O Dickinson,et al.  Risk of cardiovascular disease measured by carotid intima-media thickness at age 49-51: lifecourse study , 2000, BMJ : British Medical Journal.

[4]  Hans Burkhardt,et al.  Using snakes to detect the intimal and adventitial layers of the common carotid artery wall in sonographic images , 2002, Comput. Methods Programs Biomed..

[5]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  A Fenster,et al.  Segmentation of carotid artery in ultrasound images: method development and evaluation technique. , 2000, Medical physics.

[7]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[8]  J. Alison Noble,et al.  A shape-space-based approach to tracking myocardial borders and quantifying regional left-ventricular function applied in echocardiography , 2002, IEEE Transactions on Medical Imaging.

[9]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[10]  C.S. Pattichis,et al.  Atherosclerotic carotid plaque segmentation , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  R H Selzer,et al.  Improved common carotid elasticity and intima-media thickness measurements from computer analysis of sequential ultrasound frames. , 2001, Atherosclerosis.

[12]  Maura Griffin,et al.  Effect of Image Normalization on Carotid Plaque Classification and the Risk of Ipsilateral Hemispheric Ischemic Events: Results from the Asymptomatic Carotid Stenosis and Risk of Stroke Study , 2005, Vascular.

[13]  J M Stevens,et al.  Patterns of brain computed tomography infarction and carotid plaque echogenicity. , 2001, Journal of vascular surgery.

[14]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[15]  D. Playford,et al.  Improved analysis of brachial artery ultrasound using a novel edge-detection software system. , 2001, Journal of applied physiology.

[16]  J. S. Suri,et al.  Plaque Imaging: Pixel to Molecular Level , 2005 .

[17]  P Pignoli,et al.  Intimal plus medial thickness of the arterial wall: a direct measurement with ultrasound imaging. , 1986, Circulation.

[18]  Laurent D. Cohen,et al.  Using Deformable Surfaces to Segment 3-D Images and Infer Differential Structures , 1992, ECCV.

[19]  T. Elatrozy,et al.  The effect of B-mode ultrasonic image standardisation on the echodensity of symptomatic and asymptomatic carotid bifurcation plaques. , 1998, International angiology : a journal of the International Union of Angiology.

[20]  B R Archer,et al.  The Joint Commission for the Accreditation of Healthcare Organizations should require that all physicians who perform fluoroscopy be credentialed in radiation management by their healthcare facility. , 2000, Medical physics.

[21]  R. Armentano,et al.  Experimental and clinical validation of arterial diameter waveform and intimal media thickness obtained from B-mode ultrasound image processing. , 1999, Ultrasound in medicine & biology.

[22]  G. Mancini,et al.  Validation of a new ultrasound method for the measurement of carotid artery intima medial thickness and plaque dimensions. , 2004, The Canadian journal of cardiology.

[23]  Christos P. Loizou,et al.  Intima media segmentation of the carotid artery , 2004 .

[24]  T Gustavsson,et al.  A new automated computerized analyzing system simplifies readings and reduces the variability in ultrasound measurement of intima-media thickness. , 1997, Stroke.

[25]  A Fenster,et al.  An automated segmentation method for three-dimensional carotid ultrasound images. , 2001, Physics in medicine and biology.

[26]  D. Altman,et al.  STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.

[27]  Sergio Shiguemi Furuie,et al.  Automatic measurement of carotid diameter and wall thickness in ultrasound images , 2002, Computers in Cardiology.

[28]  Milan Sonka,et al.  Automated design of optimal border detection criteria: learning from image segmentation examples , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[29]  A. Beckett,et al.  AKUFO AND IBARAPA. , 1965, Lancet.

[30]  Jerry L. Prince,et al.  Gradient vector flow: a new external force for snakes , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[31]  Aleksandra Mojsilović,et al.  Automatic segmentation of intravascular ultrasound images: A texture-based approach , 1997, Annals of Biomedical Engineering.

[32]  C.P. Loizou,et al.  Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery , 2005, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[33]  Andrew Nicolaides,et al.  Ultrasound imaging in the analysis of carotid plaque morphology for the assessment of stroke. , 2005, Studies in health technology and informatics.

[34]  Liexiang Fan,et al.  A semiautomated ultrasound border detection program that facilitates clinical measurement of ultrasound carotid intima-media thickness. , 2005, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[35]  Michael Brady,et al.  Segmentation of ultrasound B-mode images with intensity inhomogeneity correction , 2002, IEEE Transactions on Medical Imaging.

[36]  Christos P. Loizou,et al.  Quality evaluation of ultrasound imaging in the carotid artery , 2004 .

[37]  Tomas Gustavsson,et al.  A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images , 2000, IEEE Transactions on Medical Imaging.

[38]  Lars Kai Hansen,et al.  Quantitative analysis of ultrasound B-mode images of carotid atherosclerotic plaque: correlation with visual classification and histological examination , 1998, IEEE Transactions on Medical Imaging.

[39]  A Schmidt-Trucksäss,et al.  Computerized analysing system using the active contour in ultrasound measurement of carotid artery intima-media thickness. , 2001, Clinical physiology.

[40]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[41]  ISAAC COHEN,et al.  Using deformable surfaces to segment 3-D images and infer differential structures , 1992, CVGIP Image Underst..

[42]  Arno W. Hoes,et al.  Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam Study. , 1997, Circulation.

[43]  Pong C. Yuen,et al.  A contour detection method: Initialization and contour model , 1999, Pattern Recognit. Lett..

[44]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[45]  Christos P. Loizou,et al.  Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering , 2006, Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521).

[46]  Jiankang Wang,et al.  Guiding ziplock snakes with a priori information , 2003, IEEE Trans. Image Process..