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改进的肝脏软组织分割算法及实时绘制 被引量：1

An improved method for medical liver segmentation and real-time rendering
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摘要 提出了一种基于GraphCut算法的高精度CT肝脏软组织分割算法，并利用开放运算语言（OpenCL）实现了肝脏软组织实时高效绘制。这种改进的GraphCut算法分割准确度高，平均正确率达到96．2％，而且利用OpenCL实现的基于八叉树的改进RayCasting算法大大提升了并行绘制速度，得到了近于200倍的加速，从而为实现实时跨平台虚拟手术系统提供了有力保障，也使得医生可以更高效更准确地诊断、治疗病患，该方法有良好的实用前景。 This paper presents a medical CT image segmentation algorithm based on the Graph Cut algorithm for separa- ting the liver from other soft tissues, and realizes the effective real-time rendering of soft tissue using the open computing language （OpenCL）. The average segmentation accuracy of the improved Graph Cut algorithm can be increased to 96.2%, and the Octree-based RayCasting algorithm improved using the OpenCL can greatly raise the parallel rendering speed, which makes it possible to implement a real-time cross-platform virtual surgery system. Moreover, this method can make doctor＇s diagnosis more accurate, so it has a very good practical prospect.
作者 康飞龙 杨杰
机构地区 上海交通大学图像处理与模式识别研究所
出处 《高技术通讯》 CAS CSCD 北大核心 2011年第11期1164-1170,共7页 Chinese High Technology Letters
基金 国家自然科学基金（31100672）和上海交大医工合作基金资助项目.
关键词 GRAPH Cut算法 OpenCL语言 医学肝脏分割 RayCasting算法 八叉树 实时绘制 Graph Cut, open computing language （OpenCL）, medical liver segmentation, RayCasting, Oc- tree, real-time rendering
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献15

  • 1Esneauh S, Hraieeh N, Delabrousse E, et al. Graph cut liver segmentation for interstitial ultrasound therapy. In: Proceedings of the 29th Annual International Conference of the IEEE , Lyon, France, 2007. 5247-5250.
  • 2Boykov Y, Jolly M P. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D ima- ges. In: Proceedings of the IEEE International Confer- ence on Computer Vision, Vancouver, Canada, 2001. 105-112.
  • 3Peng B, Veksler O. Parameter selection for graph cut based image segmentation. In:Proceedings of British Ma- chine Vision Conference, 2008.
  • 4Falaco A X, Udupa J K, Samarasekara S, et al. User- steered image segmentation paradigms: Live wire and livelane. Graphical Models and Image Processing, 1998, 60 : 233 -260.
  • 5Osher S, Sethian J A. Fronts propagating with curvature dependent speed : Algorithm based on hamilton jacobi for- mulations. Journal of Computational Physics, 1988, 79 : 12-49.
  • 6Boykov Y, Funka-Lea G. Graph cuts and efficient N-D image segmentation. International Journal of Computer Vi- sion, 2006, 70(2):109-131.
  • 7Casiraghi E, Lombardi G, Pratissoli S, et al. 3D c~ -ex- pansion and graph cut algorithms for automatic liver seg- mentation from CT images. In: Proceedings of the Inter- national Conference on Knowledge-Based Intelligent Infor- mation and Engineering Systems, Vietri Sul Mare Italy, 2007. 421428.
  • 8Delong A, Boykov Y. A scalable graph-cut algorithm for N-D grids. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, USA, 2008.
  • 9Felzenszwalb P, Huttenlocher I). Efficient graph-basedimage segmentation. International Journal of Computer Vi- sion, 2004, 59(2) :167-181.
  • 10Boykov Y, Kolmogorov V. An experimental comparison of min-cut/Max-flow algorithms for energy minimization in vision. IEEE Trans on PAMI, 2004, 29(9) :1124-1137.

二级参考文献10

  • 1张治国,周越,谢凯.一种基于Mum ford-Shah模型的脑肿瘤水平集分割算法[J].上海交通大学学报,2005,39(12):1955-1958. 被引量：10
  • 2Boykov Y, Veksler O, Zabih R. Fast approximate energy minimization via graph cuts [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(11) :1222-1239.
  • 3Boykov Y, Funka-Lea G. Graph cuts and efficient N- D image segmentation [J]. International Journal of Computer Vision, 2006, 70(2) : 109-131.
  • 4Freedman D, Zhang T. Interactive graph cut based segmentation with shape priors [C]//Proceedings of the 2005 IEEE Computer Society Conference on Vision and Pattern Recognition. San Diego, CA, USA: IEEE, 2005: 755-762.
  • 5Slabaugh G, Unal G. Graph cuts segmentation using an elliptical shape prior [C]//IEEE International Conference on Image Processing. Genoa, Italy: IEEE, 2005 : 1222-1225.
  • 6Marti G, Baur C, Zambelli P Y. Optimal femoral head contour segmentation in CT images using dynamic programming [J]. Technology and Health Care, 2004, 12(4): 315-322.
  • 7Boykov Y, Kolmogorov V. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26 ( 9 ) : 1124-1137.
  • 8Cao M Y, Ye C H, Doessel O, et al. Spherical parameter detection based on hierarchical Hough transform [J]. Pattern Recognition Letters, 2006, 27 (9) 980-986.
  • 9Otsu N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems, Man and Cybernetics, 1979, 9(1): 62-66.
  • 10Rother C, Blake A, Kolmogorov V. Grabcutinteractive foreground extraction using iterated graph cuts [J]. ACM Transaction on Graphics, 2004, 23(3) : 309-314.

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高技术通讯
2011年 第11期

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