Using the Hough transform to segment ultrasound images of longitudinal and transverse sections of the carotid artery.

Automatic segmentation of the arterial lumen from ultrasound images is an important task in clinical diagnosis. In this paper, the Hough transform (HT) was used to automatically extract straight lines and circles from sequences of B-mode ultrasound images of longitudinal and transverse sections, respectively, of the carotid artery. In 10 normal subjects, the specificity and accuracy of HT-based segmentation were on average higher than 0.96 for both sections, whereas the sensitivity was higher than 0.96 in longitudinal and higher than 0.82 in transverse sections. The intima-media thickness (IMT) was also estimated from images of longitudinal sections; the corresponding validation parameters were generally higher than 0.90. To further validate the results, arterial distension waveforms (ADW) were estimated from sequences of images using the HT technique as well as motion analysis using block matching (BM). In longitudinal sections, diastolic and systolic diameters and relative diameter changes using HT and BM were not significantly different. In transverse sections, diastolic and systolic diameters were significantly lower using the HT technique; the differences were <7%. Relative diameter changes in transverse sections were not significantly different from BM-estimated ones. The HT technique was also applied to four subjects with atherosclerosis, in which sensitivity, specificity and accuracy were comparable to those of normal subjects; the low values of sensitivity in transverse sections may reflect departure from the circular model because of the presence of plaque. In conclusion, the HT technique provides a reliable way to segment ultrasound images of the carotid artery and can be used in clinical practice to estimate indices of arterial wall physiology, such as the IMT and the ADW.

[1]  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.

[2]  Mark S. Nixon,et al.  Dynamic feature extraction via the velocity Hough transform , 1997, Pattern Recognit. Lett..

[3]  T Gustavsson,et al.  Ultrasound measurement of wall thickness in the carotid artery: fundamental principles and description of a computerized analysing system. , 1991, Clinical physiology.

[4]  D. Sackett,et al.  Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis. , 1991, The New England journal of medicine.

[5]  Peter Graham Fish Physics and Instrumentation of Diagnostic Medical Ultrasound , 1990 .

[6]  B. Sonesson,et al.  Diameter and compliance in the human common carotid artery--variations with age and sex. , 1995, Ultrasound in medicine & biology.

[7]  J M Carreira,et al.  Automatic calculation of total lung capacity from automatically traced lung boundaries in postero-anterior and lateral digital chest radiographs. , 1998, Medical physics.

[8]  Jack Sklansky,et al.  Finding circles by an array of accumulators , 1975, Commun. ACM.

[9]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[10]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  C. Metz Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[12]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[13]  J. Salonen,et al.  Progression of carotid atherosclerosis and its determinants: a population-based ultrasonography study. , 1990, Atherosclerosis.

[14]  Spyretta Golemati,et al.  Carotid artery wall motion estimated from B-mode ultrasound using region tracking and block matching. , 2003, Ultrasound in medicine & biology.

[15]  Aaron Fenster,et al.  A real-time biopsy needle segmentation technique using Hough transform. , 2003, Medical physics.

[16]  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.

[17]  F. Chong,et al.  Non-invasive assessment of arterial distension waveforms using gradient-based Hough transform and power Doppler ultrasound imaging , 2006, Medical and Biological Engineering and Computing.

[18]  Yang Xin,et al.  Segmentation in Echocardiographic Sequences using Shape-based Snake Model Combined with Generalized Hough Transformation , 2005, The International Journal of Cardiovascular Imaging.

[19]  A. Buchan,et al.  *North American Symptomatic Carotid Endarterectomy Trial (NASCET) Steering Committee. Beneficial Effect of Carotid Endarterectomy in Symptomatic Patients with High-Grade Carotid Stenosis. , 1991 .

[20]  J. Stoitsis,et al.  Carotid Artery Motion Estimation from Sequences of B-mode Ultrasound Images: Effect of Dynamic Range and Persistence , 2006, Proceedings of the 2006 IEEE International Workshop on Imagining Systems and Techniques (IST 2006).

[21]  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.

[22]  A Fenster,et al.  Accuracy and variability assessment of a semiautomatic technique for segmentation of the carotid arteries from three-dimensional ultrasound images. , 2000, Medical physics.

[23]  Yalin Zheng,et al.  Automated segmentation of lumbar vertebrae in digital videofluoroscopic images , 2004, IEEE Transactions on Medical Imaging.

[24]  M. Eliasziw,et al.  The causes and risk of stroke in patients with asymptomatic internal-carotid-artery stenosis. North American Symptomatic Carotid Endarterectomy Trial Collaborators. , 2000, The New England journal of medicine.

[25]  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..

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

[27]  C. Warlow,et al.  MRC European Carotid Surgery Trial: interim results for symptomatic patients with severe (70-99%) or with mild (0-29%) carotid stenosis , 1991, The Lancet.

[28]  J. Stoitsis,et al.  Comparison of B-mode, M-mode and Hough transform methods for measurement of arterial diastolic and systolic diameters , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[29]  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.

[30]  J. Alison Noble,et al.  Ultrasound image segmentation: a survey , 2006, IEEE Transactions on Medical Imaging.

[31]  Rangaraj M. Rangayyan,et al.  Automatic identification of the pectoral muscle in mammograms , 2004, IEEE Transactions on Medical Imaging.

[32]  Frédéric Zana,et al.  A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform , 1999, IEEE Transactions on Medical Imaging.

[33]  Constantinos S. Pattichis,et al.  Texture-based classification of atherosclerotic carotid plaques , 2003, IEEE Transactions on Medical Imaging.

[34]  Michael G. Strintzis,et al.  Tracking the left ventricle in echocardiographic images by learning heart dynamics , 1999, IEEE Transactions on Medical Imaging.

[35]  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.

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