[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.
|