Adjusting the input ultrasound image data and the atherosclerotic plaque detection in the carotid artery by the FOTOMNG system

. 2014 May 04 ; 28 (3) : 567-575. [epub] 20140710

Status PubMed-not-MEDLINE Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid26019544

Stroke is the third most frequent cause of death. Specifically, ischemic stroke accounts for the largest group of this kind of cases. Despite all the advances in medical therapeutic methods, no methods that would reliably reduce mortality from ischemic stroke have been found. Prevention is still the most significant way to combat stroke. When the frequent cause of ischemic stroke is atherosclerotic plaque in the carotid artery, its exploration can help to determine the development of the disease. These problems were very extensively discussed in October 2013 during the XVI International Neurosonology Congress in Sofia organized under the auspices of World Research Neurosonology Group, Bulgarian Neurosonology and Cerebral Hemodynamics Association. Our goal was to develop special modules for carotid artery picture processing (AVI file processing, reparation and reconstruction) and modules containing tools for automated carotid artery plaque detection; and to solve its measurement and three-dimensional modelling of the carotid artery and the plaque. New modules were implemented into the FOTOMNG system and tested on appropriate input data files, which verified their functionality and applicability.

Zobrazit více v PubMed

XVI . World Neurology Congress organized under the auspices of the World Neurosonology Research Group, Bulgarian Association of Neurosonology and Cerebral Hemodynamics. Sofia, Bulgaria: Sofia, Bulgary: 2013 Oct. http://students.mu-varna.bg/index.php/novini/889-svetovenkonres-nevro-son October. Available from.

Bar M. Roubec M. Farana R. Ličev L. Školoudík D. Inter-rater agreement in carotid atherosclerotic plaque evaluation by 3D ultrasound. Cerebrovasc Dis. 2013;35:390.

Ličev L. Tomeček J. Farana R. Adjusting the input image data to the ultrasound images and the detection of atherosclerotic plaque in the carotid artery within FOTOMNG system [motion picture] http://www.cs.vsb.cz/licev/experiments/test4.zip Available from. PubMed PMC

Loizou C. Ultrasound image analysis of the carotid artery [dissertation] London: School of Computing and Information Systems, Kingston University; 2005.

Moursi SG. El-Sakka Mahmoud R. 2007 IEEE International Symposium on Signal Processing and Information Technology. 2007 December 15–18. Initial contour for ultrasound carotid artery snakes; pp. 390–395.

Stoitsis J. Golemati S. Kendros S. Nikita KS. Wu Q. Sun Y. Automated detection of the carotid artery wall in B-mode ultrasound images using active contours initialized by the Hough transform. New York: (NY): Institute of Electrical and Electronics Engineers; 2008. PubMed

Xu C. Prince JL. IEEE Proceedings Conference on Computer Vision and Pattern Recognition. 1997 June 17. Gradient vector flow: a new external force for snakes; pp. 66–71. San Juan, PR.

Abdel-Dayem Amr R. Detection of arterial lumen in sonographic images based on active contours and diffusion filters. New York: (NY): Institute of Electrical and Electronics Engineers; 2010.

Yang Xin. Ding Mingyue. Lou Liantang. Ming Yuchi. Wu Qiu. Sun Yue. Common carotid artery lumen segmentation in B-mode ultrasound transverse view images. New York(NY): Institute of Electrical and Electronics Engineers; 2010.

Hassan Mehdi. Chaudhry Asmatullah. Khan Asifullah. Kim Jin Young. Carotid artery image segmentation using modified spatial fuzzy c-means and ensemble clustering. Comput Methods Programs iBiomed. 2012;108(3):1261–1276. doi: 10.1016/j.cmpb.2012.08.011. http://linkinghub.elsevier.com/retrieve/pii/S0169260712001939 Available from. PubMed DOI

Říha Kamil. MAŠEK Jan. BURGET Radim. BENEŠ Radek. ZÁVODNÁ Eva. Novel method for localization of common carotid artery transverse section in ultrasound images using modified Viola-Jones Detector. Ultrasound Med. 2013;39(10):1887–1902. doi: 10.1016/j.ultrasmedbio.2013.04.013. http://linkinghub.elsevier.com/retrieve/pii/S0301562913007199 Available from. PubMed DOI

Cootes T.F. Taylor C.J. Cooper D.H. Graham J. Active shape models-their training and application. Comput Vis Image Understanding. 1995;61:38–59.

Yang Xin. JIN Jiaoying. XU Mengling. WU Huihui. HE Wanji. YUCHI Ming. DING Mingyue. Ultrasound common carotid artery segmentation based on active shape model. Comput Math Methods Med. 2013;2013(10):1–11. doi: 10.1155/2013/345968. http://www.hindawi.com/journals/cmmm/2013/345968/ Available from. PubMed DOI PMC

Electrocardiogram – Wikipedia [online] 2011. http://cs.wikipedia.org/wiki/Elektrokardiogram last revised 2011 Mar 5 [cited 2011 Apr 23]. Available from.

Ličev L. Analysis, modeling, detection and visualization of the measurement of objects in images. 1st ed. Brno: Computer Press; 2010. p. 125.

Loizou C. Pattichis C. Panziaris M. Ultrasound image analysis of the carotid artery. Medical & Biological Engineering & Computing. 2007;45(1):35–49. PubMed

Szabo T. Poušek L. Diagnostic ultrasound imaging: inside out. 1. vyd. Boston(MA): Elsevier Academic Press; 2004. p. xxii, 549.

Ali M. Magee DA. Dasgupta U. Texas Instruments. 2008. Signal processing overview of ultrasound systems for medical imaging (white paper)http://www.ti.com/lit/wp/sprab12/sprab12.pdf [cited 2013 Mar 10]. Available from.

Pizer SM. Amburn EP. Austin JD. Adaptive histogram equalization and its variations. Comput Vis Graphics Image Process. 1987;39:355–368.

Yongjian Y. Acton ST. Speckle reducing anisotropic diffusion. IEEE Trans Image Process. 2002;11(11):1260–1270. PubMed

Sivakumar R. Gayathri MK. Nedumaran D. Speckle filtering of ultrasound B-scan images. Open Systems (ICOS) IEEE Conference; 2010 December 5–7. Kuala Lumpur (MAL)

Jan J. Medical image processing, reconstruction and restoration: concepts and methods. Boca Raton: (FL): Taylor & Francis; 2006.

Xu Ch. Snake: shapes and gradient vector flow. IEEE Trans Image Process. 1998;7:359–369. PubMed

Crandall R. Image segmentation using the Chan-Vese algorithm. 2009. p. 23.http://math.arizona.edu/~rcrandall/ECE532_ProjectPaper.pdf The University of Arisona [online] [cited 2013 Mar 14]. Available from.

Wu Y, editor. Rex's tribe of image processing. 2009. https://sites.google.com/site/rexstribeofimageprocessing/Home online. [cited 2013 Mar 17]. Available from.

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...