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基于统计变形模型的三维生物医学数据恢复 被引量:2

3D Biomedical Data Restoration Based on Statistical Deformable Model
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摘要 给出一种基于统计变形模型的生物医学数据恢复算法。该算法统计模型分为已知和未知两部分,利用统计模型构成的先验信息和待恢复数据的已知部分估算数据的未知部分。肝脏边缘缺失数据恢复实验结果表明,只要待恢复点控制在40%以下,并采用适当的分辨率,就可以将恢复误差控制在1%以内。 A biomedical data restoration algorithm based on statistical deformable model is proposed. Specifically, the statistical model is partitioned into known and unknown parts, and the unknown data are estimated by the prior knowledge constructed by the statistical model and the known data. Experiments on missing liver edge points demonstrate that the restoration error can be controlled at less than 1% under 40% unknown data points with proper resolution.
出处 《计算机工程》 CAS CSCD 北大核心 2009年第7期209-211,共3页 Computer Engineering
基金 国家自然科学基金资助重点项目(60736008) 西北大学研究生创新基金资助项目(07YJC15)
关键词 统计变形模型 主动形状模型 数据恢复 statistical deformable model active shape model data restoration
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  • 1Seong L, Yong J, Sung Y. Automatic Liver Segmentation for Volume Measurement in CT Images[J]. Journal of Visual Communication and Image Representation, 2006, 17(4): 860-875.
  • 2Zijdenbos A P, Dawant B M. Brain Segmentation and White Matter Lesion Detection in MR Images[J]. Critical Reviews in Biomedical Engineering, 1994, 22(5): 401-466.
  • 3Lorensen W E, Cline H E. Marching Cubes: A High Resolution 3D Surface Construction Algorithm[J]. Computer Graphics, 1987, 21(4): 169-169.
  • 4Castleman K R. Digital Image Processing[M]. [S.l.]: Prince Hall, 1996.
  • 5Udupa J K, Samarasekera S. Fuzzy Connectedness and Object Definition: Theory, Algorithms and Application in Image Segmentation[J]. Graphical Models and Image Processing, 1996, 58(3): 246-261.
  • 6Hadziavdic V. A Comparative Study of Active Contour Models for Boundary Detection in Brain Images[D]. Tromso, Norway: University of Tromso. 2000.
  • 7Hum M A, Mardia K V. Bayesian Fused Classification of Medical Images[J]. IEEE Transaction on Medical Imaging, 1996, 15(6): 850-858.
  • 8Worring M, Smeulders A W M. Parameterized Feasible Boundaries in Gradient Vector Fields[J]. Computer Vision and Image Understanding, 1996, 63(1): 35-144.
  • 9Chen Ting, Metaxas D. A Hybrid Framework for 3D Medical Image Segmentation[J]. Medical Image Analysis, 2005, 9(6): 547-565.
  • 10Berar M, Desvignes M, Bailly G, et al. 3D Semi-landmarks-based Statistical Face Reconstruction[J]. Journal of Computing and Information Technology, 2006, 14(1): 31-43.

同被引文献45

  • 1Philippe MERLOZ,吴昊.计算机辅助外科手术的基本概念[J].中国修复重建外科杂志,2006,20(3):276-278. 被引量:16
  • 2张利军,刘文勇,王田苗,胡磊.基于C型臂的Tomosynthesis快速重建方法[J].北京航空航天大学学报,2006,32(9):1113-1116. 被引量:2
  • 3何晓乾,陈雷霆,沈彬斌,房春兰.医学图像三维分割技术[J].计算机应用研究,2007,24(2):13-16. 被引量:16
  • 4Kass M, Witkin A, Terzopoulos D. Snakes: active contour models [J]. International Journal of Computer Vision, 1988,1 (4) : 321- 331.
  • 5Cootes T F, Taylor C J, Cooper D H. Active shape models-their training and applications [ J ] . Computer Vision and Image Understanding, 1995,61 ( 1 ) : 38-59.
  • 6Hill A, Thornham A, Taylor C J. Model-based interpretation of 3-D medical images [ C]//Proceedings of the 4th British Machine Vision Conference. Guildford, England: the British Machine Vision Association, 1993 : 339-348.
  • 7Cootes T F,Taylor C J. Combining point distribution models with shape models based on finite element analysis [ J]. Image and Vision Computing. 1995,13 (5) : 403-409.
  • 8Brett A D, Taylor C J. A method of automated landmark generation for automated 3-D PDM construction [J]. Image Vision Computing, 2000,18 ( 9 ) : 739- 748.
  • 9Kelemen A, Szekely G, Gerig G. Three- dimensional model-based segmentation of Brain MRI [ J]. IEEE Transactions on Medical Imaging, 1999,18 ( 10 ) : 828- 839.
  • 10Rueckert D, Frangi A F, Schnabel J A. Automatic construction of 3D statistical deformation models using non-rigid registration [ C ] //Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention. Berlin, Heidelberg, German: Springer LNCS 2208, 2001:77-84.

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