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血管內(nèi)超聲圖像邊緣提取方法的研究進(jìn)展

Progress in the Arithmetic of IVUS Image Segmentation

作者: 汪友生  舒毓  陳建新 
單位:北京工業(yè)大學(xué)電控學(xué)院(北京100124)
關(guān)鍵詞: 血管內(nèi)超聲;預(yù)處理;邊緣檢測(cè);活動(dòng)輪廓模型 
分類號(hào):
出版年·卷·期(頁(yè)碼):2010·29·3(312-317)
摘要:

血管內(nèi)超聲圖像在心血管疾病的診斷和介入治療中具有重要作用,超聲圖像的邊緣提取有很強(qiáng)的現(xiàn)實(shí)意義。但超聲頻率的提高加大了噪聲的影響,增加了血管壁內(nèi)外膜邊緣提取的難度。本文從預(yù)處理、檢測(cè)模型以及算法實(shí)現(xiàn)三方面,回顧了近幾年血管壁邊緣提取的發(fā)展情況和研究動(dòng)態(tài),并對(duì)未來(lái)的發(fā)展方向進(jìn)行了總結(jié)和展望。

Intravascular ultrasound (IVUS) plays an important role in the diagnosis of cardiovascular diseases and interventional treatment. The edge detection of IVUS image has a strong practical significance. However, the improvement of ultrasonic frequency increases the noise impact, and increases the difficulty for extracting the edges of the vessel wall intima and adventitia. This paper reviews the research and development of IVUS image edge detection from pre-process, detection models and algorithms in recent years, and prospects the future direction of development for IVUS image edge detection.

參考文獻(xiàn):

[1]葛均波主編.血管內(nèi)超聲多普勒學(xué).人民衛(wèi)生出版社,北京:2000:30-31.
[2]Suiji Li, The Diagnostic and Therapeutic Significance of MSCT, CAG and IVUS in CAD , OCT.2008.http://epu b.cnki.net/grid2008/detail.aspx?filename=2008128098.nh&dbname=CMFD2008.
[3]Feyter P J,Nieman K.New Coronary. Imaging Techniques:What to Expect?Heart,2002,87:195-197.
[4]Palnr,Palsk.A Review on Image Segmentation Techniques,Pattern Recognition, 1993,26(9):277-294.
[5]Qi Zhang,Weiqi Wang.Contour Extraction from IVUS Images Based on GVF Snakes and Wavelet Transform.IEEE/ICME International Conference,2007,5:536-541.
[6]李虹,王惠南,董海艷,等.基于小波變換的血管內(nèi)超聲圖像血流斑點(diǎn)噪聲抑制研究.生物醫(yī)學(xué)工程學(xué)雜志,2008,25(2):313-317.
[7]李虹,王惠南,邵小麗.基于小波變換的IVUS圖像去噪.中國(guó)醫(yī)療器械信息,2007,13 (3):8-10.
[8]熊先越,張汗靈. 基于邊緣檢測(cè)的空間自適應(yīng)小波去噪.計(jì)算機(jī)工程與應(yīng)用,2006,42(7) :59-61.
[9]孫豐榮,劉澤,李艷玲,等.一種改進(jìn)的自適應(yīng)形變模型及其血管內(nèi)超聲圖像的邊緣提取應(yīng)用.中國(guó)生物醫(yī)學(xué)工程學(xué)報(bào), 2008,27(2):276-281.
[10]董海艷,王惠南,陶玲.基于血管內(nèi)超聲圖像的時(shí)空相關(guān)性的血流斑點(diǎn)去噪方法.生物醫(yī)學(xué)工程學(xué)雜志, 2006,23(6):1213-1217.
[11]Gerardo Mendizabal-Ruiz, Mariano Rivera and Ioannis A. Kakadiaris.A probabilistic segmentation method for the identification of luminal borders in intravascular ultrasound images. 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008,1-8.
[12]王昱鑌,毛征,雷加印,等.基于熵和GVF的血管內(nèi)超聲圖像邊緣檢測(cè). 國(guó)外電子測(cè)量,2008,11:14-16.
[13]Kass M. Witkin A,Terzopoulos D. Snakes: active contour models.International Journal of Computer Vision,1987,1:321-331.
[14]裘振,汪源源,王威琪,等.利用Rayleigh模型和B-snake自動(dòng)提取冠脈內(nèi)超聲圖像管腔輪廓.上海生物醫(yī)學(xué)工程,2006,26(1):3-6.
[15]Unal G, Bucher S, Carlier S,et al. Shape-driven Segmentation of Intravascular Ultrasound Images. Proc. of 1st International Workshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII 2006):51–58.
[16]Brusseau E., de Korte C L,Mastik  F, et al. Fully automatic luminal  contour  segmentation  in  intracoronary  ultrasound  imaging-A statistical approach. IEEE Trans Medical Imaging, 2004, 23(5) :554-566. .
[17]曲懷敬,孫豐榮,李艷玲,等.基于活動(dòng)輪廓模型和統(tǒng)計(jì)特征的血管內(nèi)超聲圖像的邊緣提取.中國(guó)圖象圖形學(xué)報(bào), 2005,10(8):999-1004.
[18]Yousheng Wang,Yu Shu,Baile Hu et al,An improved level set method of ultrasound imaging to detect blood vessel walls.International Conference on Image Analysis and Signal Processing, 2009:28-31.
[19]Christian Perrey, Ulrich Scheipers, Waldemar Bojara.Computerized Segmentation of Blood and Luminal Borders in Intravascular Ultrasound.2004 IEEE International Ultrasonics, Ferroelectrics, and Frequency Control Joint 50th Anniversary Conference:1122-1125.
[20]Amini A, Weymouth T E, Jain RC.Using dynamic programming for solving variational problems in vision. IEEE Trans Pattern Analysis And Machine Intelligence,1990, 12(9): 855-867.
[21]Zhu Yan, Hong Yan. Computerized tumor boundary detection using a Hopfield neural network. Medical Imaging, IEEE Transactions ,1997, 16(1): 55-67.
[22]Plissiti M E, Fotiadis D I,George E,et al.An Automated Method for Lumen and Media-Adventitia B order Detection in a Sequence of IVUS Frames .IEEE Transactions on Information Technology in Biomedicine, 2004,8(2):131-141.
[23]Marie-Helene Roy Cardinal, Jean Meunier, Gilles Soulez,et al.Intravascular Ultrasound Image Segmentation: A Three-Dimensional Fast-Marching Method Based on Gray Level Distributions. IEEE Transactions on Medical Imaging,2006,25(5):590-601.
[24]Williams DJ,Shah MA.A Fast Algorithm for Active Contours and Curvature Estimation CVGIP: Image Understanding, 1992,55:14-26.

 

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