A DYNAMIC FINITE-ELEMENT SURFACE MODEL FOR SEGMENTATION AND TRACKING IN MULTIDIMENSIONAL MEDICAL IMAGES WITH APPLICATION TO CARDIAC 4D IMAGE-ANALYSIS

被引:247
作者
MCINERNEY, T
TERZOPOULOS, D
机构
[1] Department of Computer Science, University of Toronto, Toronto
基金
加拿大自然科学与工程研究理事会;
关键词
3D/4D MEDICAL IMAGE ANALYSIS; DEFORMABLE MODELS; FINITE ELEMENTS; DYNAMICS; CARDIAC LV SEGMENTATION; NONRIGID MOTION TRACKING; VISUALIZATION; INTERACTION;
D O I
10.1016/0895-6111(94)00040-9
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper presents a physics-based approach to anatomical surface segmentation, reconstruction, and tracking in multidimensional medical images. The approach makes use of a dynamic ''balloon'' model-a spherical thin-plate under tension surface spline which deforms elastically to fit the image data. The fitting process is mediated by internal forces stemming from the elastic properties of the spline and external forces which are produced from the data. The forces interact in accordance with Lagrangian equations of motion that adjust the model's deformational degrees of freedom to fit the data. We employ the finite element method to represent the continuous surface in the form of weighted sums of local polynomial basis functions. We use a quintic triangular finite element whose nodal variables include positions as well as the first and second partial derivatives of the surface. We describe a system, implemented on a high performance graphics workstation, which applies the model fitting technique to the segmentation of the cardiac LV surface in volume (3D) CT images and LV tracking in dynamic volume (4D) CT images to estimate its nonrigid motion over the cardiac cycle. The system features a graphical user interface which minimizes error by affording specialist users interactive control over the dynamic model fitting process.
引用
收藏
页码:69 / 83
页数:15
相关论文
共 31 条
  • [1] Carlbom, Terzopoulos, Harris, Computer-assisted registration, segmentation, and 3D reconstruction from images of neuronal tissue sections, IEEE Trans. Med. Imaging, 13, 2, pp. 351-362, (1994)
  • [2] Lorenson, Cline, Marching cubes a high resolution 3D surface construction algorithm, ACM SIGGRAPH Computer Graphics, 21, 4, pp. 163-169, (1987)
  • [3] Sander, Zucker, Inferring surface trace and differential structure from 3D images, IEEE Trans. Pattern Anal. Machine Intell., 12, 9, pp. 833-854, (1990)
  • [4] Sternberg, Grayscale morphology, Comput. Vision Graph. Image Process, 35, pp. 333-355, (1986)
  • [5] Drebin, Carpenter, Hanrahan, Volume Rendering, Comput. Graph., 22, 4, pp. 65-74, (1988)
  • [6] Terzopoulos, Witkin, Kass, Constraints on deformable models: Recovering 3D shape and nonrigid motion, Artif. Intell., 36, 1, pp. 91-123, (1988)
  • [7] Terzopoulos, Metaxas, Dynamic 3D models with local and global deformations: Deformable superquadrics, IEEE Trans. Pattern Anal. Machine Intell., 13, 7, pp. 703-714, (1991)
  • [8] Pentland, Horowitz, Recovery of nonrigid motion and structure, IEEE Trans. Pattern Anal. Machine Intell., 13, 7, pp. 730-742, (1991)
  • [9] Cohen, On active contour models and balloons, CVGIP: Image understanding, 53, 2, pp. 211-218, (1991)
  • [10] Delingette, Hebert, Ikeuchi, Shape representation and image segmentation using deformable surfaces, Proceedings IEEE conference computer vision and pattern recognition, pp. 467-472, (1991)