No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
1.B. E. Hirsch, J. K. Udupa, and E. Stindel, Tarsal joint kinematics via 3D imaging, in 3D Imaging in Medicine, 2nd ed. (CRC, Boca Raton, FL, 2000), Chap. 9.
2.J. K. Udupa, B. E. Hirsch, S. Samarasekera, and R. Goncalves, “Joint kinematics via 3-D MR imaging,” in Visualization in Biomedical Computing, Proc. SPIE 1808, 664–670 (1992).
3.S. V. Sint Jan, D. J. Giurintano, D. E. Thompson, and M. Rooze, “Joint kinematics simulation from medical imaging data,” IEEE Trans. Biomed. Eng. 44, 1175–1184 (1997).
4.R. M. Fiepel, “Three-dimensional motion patterns of the carpal bones: An in-vivo study using three-dimensional computed tomography and clinical applications,” Surg. Radiol. Anat. 21(2), 165–170 (1999).
5.B. M. You, P. Siy, W. Anderst, and S. Tashman, “In vivo measurement of 3-D skeletal kinematics from sequences of biplane radiographs: Application to knee kinematics,” IEEE Trans. Med. Imaging 20(6), 514–525 (2001).
7.M. D. Fuente, J. A. Ohnosorge, E. Schkommodau, S. Jetzki, D. C. Wirtz, and K. Radermacher, “Fluoroscopy-based 3-D reconstruction of femoral bone cement: A new approach for revision total hip replacement,” IEEE Trans. Biomed. Eng. 52(4), 664–675 (2005).
8.J. X. Chen, H. Wechsler, J. Mark Pullen, Y. Zhu, and E. B. Macmahon, “Knee surgery assistance: Patient model construction, motion simulation, and biomechanical visualization,” IEEE Trans. Biomed. Eng. 48(9), 1042–1052 (2001).
11.J. Sethian, Level Set Methods and Fast Marching Methods (Cambridge University Press, Cambridge, 1996).
12.L. Vincent and O. Soille, “Watersheds in digital spaces: An efficient algorithm based on immersion simulations,” IEEE Trans. Pattern Anal. Mach. Intell. 13(6), 583–598 (1992).
13.Y. Boykov, O. Veksler, and R. Zabih, “Fast Approximate Energy Minimization via Graph Cuts,” International Conference on Computer Vision, Kerkyra, Corfu, Greece, pp. 377–384 (1999).
14.E. Diday and J. C. Simon, “Clustering analysis,” in Digital Pattern Recognition (Springer-Verlag, Berlin, 1980), pp. 47–94.
15.J. K. Udupa and S. Samarasekera, “Fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation,” Graph. Models Image Process. 58(3), 246–261 (1996).
16.B. Dogdas, D. W. Shattuck, and R. M. Leahy, “Segmentation of the skull in 3D human MR images using mathematical morphology,” Proc. SPIE 4684, 1553–1562 (2002).
17.M. Bomans, K. H. Hoehne, and M. Riemer, “3D segmentation of MR images of the head for 3D display,” IEEE Trans. Med. Imaging 9(2), 177–183 (1990).
18.T. Heinonen, H. Eskola, P. Dastidar, P. Laarne, and J. Malmivuo, “Segmentation of T1 MR scans for reconstruction of resistive head models,” Comput. Methods Programs Biomed. 54, 173–181 (1997).
19.L. Lorigo, O. Faugeras, E. Grimson, and R. Keriven, “Segmentation of bone in clinical knee MRI using texture-based geodesic active contours,” Medical Image Computation and Computer Assisted Interventions, Boston, October, 1998.
20.T. B. Sebastian, H. Tek, J. J. Crisco, and B. B. Kimia, “Segmentation of carpal bones from CT images using skeletally coupled deformable models,” Med. Image Anal. 70(1), 21–45 (2003).
21.C. C. Reyes-Aldasoro and A. Bhalerao, “Sub-band filtering for MR Texture Segmentation,” Medical Image Understanding and Analysis, Portsmouth, U.K., July, 2002, pp. 22–23.
22.V. Grau, A. U. M. Mewes, M. Alcaniz, R. Kikinis, and S. K. Warfield, “Improved watershed transform for medical image segmentation using prior information,” IEEE Trans. Med. Imaging 23(4), 447–458 (2004).
23.A. X. Falcao, J. K. Udupa, S. Samarasekera, and S. Sharma, “User-steered image segmentation paradigms: Live wire and live lane,” Graph. Models Image Process. 60, 233–260 (1998).
24.M. Holden, J. A. Schnabel, and D. L. Hill, “Quantification of small cerebral ventricular volume changes in treated growth hormone patients using non-rigid registration,” IEEE Trans. Med. Imaging 21(10), 1292–1301 (2002).
25.G. Calmon and N. Roberts, “Automatic measurement of changes in brain volume on consecutive 3D MR images by segmentation propagation,” Magn. Reson. Imaging 18(4), 439–453 (2000).
26.S. Siegler, J. K. Udupa, S. I. Ringleb, C. W. Imhauser, B. E. Hirsch, D. Odhner, P. K. Saha, E. Okereke, and N. Roach, “Mechanics of the ankle and subtalar joints revealed through a three dimensional stress MRI technique,” J. Biomech. 38(3), 567–578 (2005).
27.R. C. Rhoad, J. J. Klimkiewicz, G. R. Williams, S. B. Kesmodel, J. K. Udupa, J. B. Kneeland, and J. P. Iannotti, “A new in vivo technique for 3D shoulder kinematics analysis,” Skeletal Radiol. 27, 92–97 (1998).
28.S. Simon, M. Davis, D. Odhner, J. Udupa, and B. Winkelstein, “CT imaging techniques for describing motions of the cervicothoracic junction and cervical spine during flexion, extension, and cervical traction,” Spine (in press).
29.T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham, “Active shape models their training and application,” Comput. Vis. Image Underst. 61, 38–59 (1995).
30.T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001).
31.J. Liu, J. K. Udupa, P. K. Saha, D. Odhner, B. E. Hirsch, S. Siegler, S. Simon, and B. A. Winkelstein, “Model-based 3D segmentation of the bones of joints in medical images,” Proc. SPIE (in press, 2005).
32.J. P. W. Pluim, J. B. Antoine Maintz, and M. A. Viergever, “Mutual information based registration of medical images: A survey,” IEEE Trans. Med. Imaging 22(8), 986–1004 (2003).
33.K. D. Toennies, J. K. Udupa, G. T. Herman, I. L. Wornom, and S. R. Buchman, “Registration of 3D objects and surfaces,” IEEE Comput. Graphics Appl. 10(3), 52–62 (1990).
34.J. K. Udupa, “Multidimensional digital boundaries,” Graph. Models Image Process. 56(4), 311–323 (1994).
35.G. J. Grevera, J. K. Udupa, and D. Odhner, “An order of magnitude faster surface rendering in software on a PC than using dedicated rendering hardware,” IEEE Trans. Vis. Comput. Graph. 6(4), 335–345 (2000).
37.M. J. D. Powell, UOBYQA: Unconstrained optimization by quadratic approximation, Math. Program, DOI 10.1007/s101070100290.
38.J. K. Udupa, V. R. LeBlanc, Y. Zhuge, C. Imielinska, H. Schmidt, B. E. Hirsch, and J. Woodburn, “A framework for evaluating image segmentation algorithms,” Comput. Med. Imaging Graph. 30(2), 75–87 (2006).
39.J. K. Udupa, B. E. Hirsch, H. J. Hillstrom, G. R. Bauer, and J. B. Kneeland, “Analysis of in vivo 3-D internal kinematics of the joints of the foot,” IEEE Trans. Biomed. Eng. 45, 1387–1396 (1998).
40.J. K. Udupa, D. Odhner, S. Samarasekera, R. Goncalves, K. Iyer, K. Venugopal, and S. Furuie, “3DVIEWNIX: An open, transportable, multidimensional, multimodality, multiparametric imaging software system,” Proc. SPIE 2164, 58–73 (1994).
41.P. K. Saha and J. K. Udupa, “Isoshaping rigid bodies for motion analysis,” Proc. SPIE 4684, 343–352 (2002).
42.A. Souza and J. K. Udupa, “Iterative live wire and live snake: New user-steered 3D image segmentation paradigms,” Proc. SPIE 6144, 1159–1165 (2006).
Article metrics loading...
Full text loading...
Most read this month