Elasticity detection of IMT of Common carotid Artery
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International Journal of Computer & Organization Trends (IJCOT) | |
© 2011 by IJCOT Journal | ||
Volume-1 Issue-3 |
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Year of Publication : 2011 | ||
Authors : V.Savithri,Dr.S.Purushothaman |
Citation
V.Savithri,Dr.S.Purushothaman. "Elasticity detection of IMT of Common carotid Artery" International Journal of Computer & organization Trends (IJCOT), V1(3):16-19 Nov - Dec 2011, ISSN 2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract
This paper presents the prediction of the amount of elasti city of a given artery for different aged pers on to obtain absolute accuracy in detection and determination of the boundary of ultrason ic carotid artery and intima - media thickness. To satisfy the requirements the most popular training algorithm , the back - propagation based generalized delta ru le ( gdr ) is developed . This procedure may simplify the job of the practitioner for analyzing accuracy and variability of segmentation results . Possible plaque regions are also highlighted . A thorough evaluation of the method in the clinic al environment shows that inter observer variability is evi dently decreased and so is the overall analys is time . The results demonstrate that it has the potential to perform qualitatively better than applying existing methods in intima and adventitial layer detection on b - mode images .
References
[1] Bing Nan Li,Chee Kong Chuti,Stephen Chang,S.H.Ong, ” Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation”,computers in Biology and Medicine 41(2011)1 - 10.
[2] N. San thiyakumari,MMadheswaran,” Intelligent medical decision system for identifying ultrasound carotid artery images with vascular Disease”, International journal of Computer Application (0975 - 8887),2010,Vol.I – No 13,pp323 9.
[3] S.C. Amartur,D.Piraino,Y.Takefuji, “Optimization neural networks for the segmentation of magnetic resonance images” IEEE Transactions in Medical imaging vol II No2 June 1992 pp215 - 220
[4] Toyota A ShimaT Nishida M Y amane K OkadaY Csiba L kollar J Sikula J “Angiographical evaluation of extracranial carotid artery comparison between Japanese and Hungarian”No to Shinkel 1997 Jul49(7) 633 - 7
[5] Marion sh L Eigenbrodt RishiSukhija Kathry nM.Rose,et al, ‘Common carotid artery wall thickness and external diameter as predictors of Prevalent and incident cardiac events in a large population study”2007 Biomed central ltd.
[6] Kanchan Deshmukh and G.N. Shinde “An ada ptive neuro fuzzy system for color image segmentation” Indian Institute Sci ,.September - October 2006,86., 493 - 506’.
[7] Kalpana saini M.L.Dewal et al. “Ultrasound imaging and image segmentation in the area of ultrasound A Revie w” International Journal Of Advanced Science and Technology Vol 24 Nov 2010. pp 41 - 59.
[8] Da - Chuan Cehng,Christian Billich et al “Automatic detection of the carotid artery boundary on crosssectional MR image sequence s using a circle model guided dynamic programming”. Biomedical enginerring oline 2011 10;26doi:10.11.86/1475 - 925X - 10 - 26 pp17
[9] HansLA Nienhuis KarinadeLeeuw et al “Small artery elasticity is decreased in patients wih systemi c lupus erythematosus without increased Intima media thickness” Biomed central ltd.2010.
[10] Wen - Xiong Kang Quing - Qiang Yang et al “The Comparative Research on Image Segmentation Algorithms”
[11] Christos P Loizou, Constan tinos S.Pattichis “An integrated System for the segmentation of Atherosclerotic Carotid Plaque” IEEETransactions on information technology in Biomedicine vol 11 No6 November 2007pp661 - 667.”
[12] S.C.Amartur D.Piraino and Y.Ta kefuji “Optimization Neural Networks for the segmentation of magnetic resonance images”. IEEE Transactions on medical imaging volII No2 June 1992 pp215 - 220
[13] Mustafa Secil, Canan Altay et al “Automated measurement of i ntimamedia thickness of carotid arteries in ultrasonagraphy by computer Software
[14] SchimdtC Wendelhag “How can the variability in ultrasound measurement of intimamedia thickness be reduced? Studies of interObservervariability incarotid and femoral arteries”.
[15] P.Pignoli,E.Tremoli et.al “Intimmal plus medial thickness of the arterial wall; a direct measurement with ultrasound imaging”
[16] K.Thangavel R.Manavalan Laurence Aroquiaraj “Removal of speckleno ise from ultrasound medical image based on special Filters; comparative study ICGSTjournal issn 1687 - 398x vol9 issue iii june 2009 pp25 - 32
[17] American Heart Association” Risk Factors identified in childhood decreased carotid ar tery elasticity inadulthood”
[18]T.Gustavasson R.Abu Gharbieh et al “Implementation and comparison of four different boundary detection algorithms for quantitive Ultrasonic measurements of the Human carotid artery” PP69 - 72
[19] David Boen “Segmenting 2D Ultrasound Images using seeded region growing”,proceed.,university of Columbia,2009.
[20] P.Abolmaesumi,M.R. Sirouspour “An interacting multiple model probabilistic data association filter for cvity boundary extraction from Ultrasound images” CITO,Project,cananda.
[21]Eric de Groot J Wouter Jukema et al “B - mode ultrasound assessment of pravastating treatment effect on carotid and femoral artery wall and its correlations with coronar y arteriographic findings; A Report of the Regression growth evaluation statin study (regress)
[22]David Wang “Fully automated common carotid artery and internal jugular vein identification and tracking using B mode ultrasou nd”.
[23]Amir A Amini Terry E Weymouth Ramesh C Jain “Using dynamic programming for solving variational problems in Vision” IEEE transactions on pattern analysis and machine intelligence vol 12 No9 september 1990 pp855 - 867
[24]P. A bolmaesumi S.E.Salcudean W.H.Zhu “Visual servoing for Robot assisted Diagnostic Ultrasound”
[25] Tineke J Smilde;Franchette W.P.J van den Berkmortel; godfried H.J. Boears et al “Carotid and Femoral artery wall thickness and stiffn es in patients at risk for cardiovascular disease with special emphasis hyperhomocysteinemia”,2008.
[26] Xiang - sun - zhang Ruishengwang et al “Minimum conflict individual haplotyping from snp fragments and related genotype”,Evoluti onary bioinformatics,2006,pp261 - 270.
[27]Xiaotao Wan J.F Pekny G.V. Reklaitis “Simulation based optimizaqtion for risk management in multistage capacity expansion”,Elsevier B.V.,2006,pp1881 - 1886.
[28]Effat Soleimani Manijhe Mokhtari Dizaj i Hajir Saberi “Carotid Artery wall motion estimation from consecutive ultrasonic images comparison Between block - matching and maximum - gradient algorithims” the journal of Tehran University Heart center,2011;6(2):72 - 78.
[29]P Abolmaesumi M.R.Sirouspur and S.E.Salcudean “Real - time extraction of carotid artery contours from ultrasound images” .
Keywords
A RTERY , BOUNDARY DETEC TION , INTIMA MEDIA THICKNESS , U LTRASONIC , PARALLEL PROGRAMMIN.