期刊文献+

一种基于ITK和VTK的肝脏管道自动分级算法

An Automatic Hepatic Vessel Classification Algorithm Based on ITK and VTK
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摘要 肝脏管道的分级是肝脏管道分支类型判定、管道变异情况分析的重要步骤,是针对性地制定个性化手术方案,从而降低肝切除手术风险的前提.基于ITK(insight segmentation and registration toolkit)和VTK(visualization toolkit)设计了一种肝脏管道自动分级的算法,实现了肝脏CT序列的管道自动提取、管道细化、管道拓扑建模以及管道分级的功能,最后用不同的颜色将不同级别的管道进行三维显示,便于医生更直观地对肝脏的管道系统的形态及结构进行分析,为制定术前手术计划提供帮助. The hepatic vessel classification is an important step in the process of the hepatic vessel branch type determination,and vessel variation analysis.It is also the premise of targeting to develop a personalized surgery program with reducing the risk of hepatic resection.In this paper,an automatic hepatic vessel classification algorithm using insight segmentation and registration toolkit(ITK) and visualization toolkit(VTK) is introduced.The algorithm implements the liver CT sequence of vessel automatic extraction,vessel thinning,vessel topology modeling,vessel classification,and the different levels of vessel coloring display in 3D aiming at facilitating the doctor much intuitively with hepatic duct system form and structure analysis to make the preoperative operation plan.
出处 《厦门大学学报(自然科学版)》 CAS CSCD 北大核心 2013年第2期190-195,共6页 Journal of Xiamen University:Natural Science
基金 国家自然科学基金青年科学基金项目(61001144)
关键词 肝脏管道 管道分级 肝脏分支类型 hepatic vessel vessel classification hepatic branch type
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参考文献25

  • 1朱明德,方驰华.肝脏管道系统变异在活体肝移植中的意义[J].肝胆外科杂志,2005,13(6):473-476. 被引量:2
  • 2Zhang Y J ,Gerbrands J J. Transition region determination based thresholding[J]. Pattern Recognition Letter, 1991, 12:13 23.
  • 3Sahoo P, Wilkinsand (', Yeager J. Threshold selection u sing Renyi's entrol?y[J]. Pattern Recognition, 1997, 30 (1) :71-84.
  • 4Manousakas I N, Undrill P E, Cameron G G, et al. SPlit and merge segmentation of magnetic resonance medical images:performance evaluation and extension to three di mensions[J]. ComPuters and Biomedical Research, 1998, 31,393-412.
  • 5Kass M, Witkin A, TerzoPoulos D. Snakes active contour models [J]. International Journal of Computer Vision, 1987,1(4) :321 331.
  • 6Osher S,Sethian J. Fronts propagating with curvature de pendent speed[J]. J Comput Phys,1988,79: 12-49.
  • 7Sethian J A. Fast marching methods[J]. SIAM Rev, 1999, 41 : 199-235.
  • 8Falcao A X, Udupa J K, Samarasekera S, et al. User- steered image segmentation paradigms live wire and live lane[J]. Graphic Models and Image Processing, 1998,60: 233 260.
  • 9周振环,王安明,王京阳.医学图像分割与配准[M].成都:电子科技大学出版社,2007.
  • 10Kapur J N,Sahoo P K,Wong A K C. A new method for gray level picture thresholding using the entropy of the histogram E J ]. Computing Vision Graphics Image Process,1985,29(3) :273 285.

二级参考文献38

  • 1Bai-Yong Shen,Hong-Wei Li,Man Chen,Min-Hua Zheng,Lu Zang,Shao-Min Jiang,Jian-Wen Li,Yu Jiang the Department of Surgery, Ruijin Hospital, Shanghai Second Medical University, Shanghai 200025, China Department of Ultrasonography, Ruijin Hospital, Shanghai Second Medical University, Shanghai 200025, China.Color Doppler ultrasonographic assessment of the risk of injury to major branch of the midddle hepatic vein during laparoscopic cholecystectomy[J].Hepatobiliary & Pancreatic Diseases International,2003,2(1):126-130. 被引量:4
  • 2金武男,杨香.螺旋CT三维重建对各肝段门静脉解剖结构的观察[J].中国医学影像技术,2003,19(6):692-695. 被引量:14
  • 3秦开怀,关右江.圆弧曲线的三次NURBS表示[J].计算机学报,1995,18(2):146-150. 被引量:23
  • 4PUDNEY C. Distance-ordered homotopic thinning: a skeletonization algorithm for 3D digital Image[J].Computer Vision and Image Understanding, 1998, 72(3) :404-413.
  • 5LEE T C,KASHYAP R L K,CHU C N. Building skeleton models via 3-D medial surface/axis thinning algorithms[J]. CVGIP: Graphical Models Image Process, 1994,56(6) :462-478.
  • 6MALANDAIN G, BERTRAND G B. Fast characterization of 3D simple points[C]. IEEE Interna tional Conference on Pattern Recognition, 1992 :232-235.
  • 7BORGEFORS G. Distance Transformations in arbitrary dimensions [J]. Computer Vision Graphics Image Process, 1984,27 : 321- 345.
  • 8LIU J Y,WANG R SH. Sketching a gray scale pattern based on non-ridge points lowering operation[J]. Journal of Image and Graphics, 2000 (5) : 544-547.
  • 9TANG T, TENG Q Z, HE X H. A hybrid reconstruction method of sandstone from 2D section image[C]. Neural Networks and Signal Processing, 2008:342-347.
  • 10韩国强,田绪红,李志垣,司徒志远.三维图像骨架化方法综述[J].小型微型计算机系统,2007,28(9):1695-1699. 被引量:9

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