Creating and Animating Subject-Specific Anatomical Models
Creating and animating subject‐specific anatomical models is traditionally a difficult process involving medical image segmentation, geometric corrections and the manual definition of kinematic parameters. In this paper, we introduce a novel template morphing algorithm that facilitates three‐dimensi...
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| Published in: | Computer graphics forum Vol. 29; no. 8; pp. 2340 - 2351 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Oxford, UK
Blackwell Publishing Ltd
01.12.2010
Wiley |
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| ISSN: | 0167-7055, 1467-8659 |
| Online Access: | Get full text |
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| Abstract | Creating and animating subject‐specific anatomical models is traditionally a difficult process involving medical image segmentation, geometric corrections and the manual definition of kinematic parameters. In this paper, we introduce a novel template morphing algorithm that facilitates three‐dimensional modelling and parameterization of skeletons. Target data can be either medical images or surfaces of the whole skeleton. We incorporate prior knowledge about bone shape, the feasible skeleton pose and the morphological variability in the population. This allows for noise reduction, bone separation and the transfer, from the template, of anatomical and kinematical information not present in the input data. Our approach treats both local and global deformations in successive regularization steps: smooth elastic deformations are represented by an as‐rigid‐as‐possible displacement field between the reference and current configuration of the template, whereas global and discontinuous displacements are estimated through a projection onto a statistical shape model and a new joint pose optimization scheme with joint limits. |
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| AbstractList | Creating and animating subject‐specific anatomical models is traditionally a difficult process involving medical image segmentation, geometric corrections and the manual definition of kinematic parameters. In this paper, we introduce a novel template morphing algorithm that facilitates three‐dimensional modelling and parameterization of skeletons. Target data can be either medical images or surfaces of the whole skeleton. We incorporate prior knowledge about bone shape, the feasible skeleton pose and the morphological variability in the population. This allows for noise reduction, bone separation and the transfer, from the template, of anatomical and kinematical information not present in the input data. Our approach treats both local and global deformations in successive regularization steps: smooth elastic deformations are represented by an as‐rigid‐as‐possible displacement field between the reference and current configuration of the template, whereas global and discontinuous displacements are estimated through a projection onto a statistical shape model and a new joint pose optimization scheme with joint limits. Creating and animating subject-specific anatomical models is traditionally a difficult process involving medical image segmentation, geometric corrections and the manual definition of kinematic parameters. In this paper, we introduce a novel template morphing algorithm that facilitates 3D modeling and parameterization of skeletons. Target data can be either medical images or surfaces of the whole skeleton. We incorporate prior knowledge about bone shape, the feasible skeleton pose, and the morphological variability in the population. This allows for noise reduction, bone separation, and the transfer, from the template, of anatomical and kinematical information not present in the input data. Our approach treats both local and global deformations in successive regularization steps: smooth elastic deformations are represented by an displacement field between the reference and current configuration of the template, while global and discontinuous displacements are estimated through a projection onto a statistical shape model and a new joint pose optimization scheme with joint limits. |
| Author | Pai, D. K. Gilles, B. Revéret, L. |
| Author_xml | – sequence: 1 givenname: B. surname: Gilles fullname: Gilles, B. organization: Department of Computer Science, University of British Columbia, Canada {bgilles@cs.ubc.ca, pai@cs.ubc.ca} – sequence: 2 givenname: L. surname: Revéret fullname: Revéret, L. organization: EVASION, INRIA Rhône-Alpes, France lionel.reveret@inrialpes.fr – sequence: 3 givenname: D. K. surname: Pai fullname: Pai, D. K. organization: Department of Computer Science, University of British Columbia, Canada {bgilles@cs.ubc.ca, pai@cs.ubc.ca} |
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| Cites_doi | 10.1016/j.cviu.2005.01.005 10.1364/JOSAA.5.001127 10.1145/1531326.1531378 10.1016/j.patcog.2006.08.012 10.1109/34.121791 10.1007/BF01901286 10.1016/S0262-8856(03)00137-9 10.1111/j.1467-8659.2008.01283.x 10.1145/1276377.1276480 10.1007/s11263-006-9966-2 10.1145/378456.378528 10.1145/566654.566626 10.1007/s11263-008-0172-2 10.1016/S1361-8415(02)00065-8 10.1145/1360612.1360696 10.1145/1531326.1531341 10.1145/1073204.1073207 10.1111/j.1467-8659.2008.01286.x 10.1007/978-1-4757-1904-8 10.1145/1618452.1618521 10.1016/S1361-8415(00)00014-1 10.1111/j.1467-8659.2008.01285.x 10.1145/1073204.1073216 10.1145/1141911.1141920 10.1145/1276377.1276478 |
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| Copyright | 2010 The Authors Computer Graphics Forum © 2010 The Eurographics Association and Blackwell Publishing Ltd. Distributed under a Creative Commons Attribution 4.0 International License |
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| References_xml | – reference: Gascuel J.-D., Cani M.-P.: Displacement constraints for interactive modeling and animation of articulated structures. The Visual Computer 10, 4 (1994), 191-204. – reference: Wang K., He Y., Qin H.: Incorporating rigid structures in non-rigid registration using triangular b-splines. VLSM (2005), 235-246. – reference: Chang W., Zwicker M.: Automatic registration for articulated shapes. Computer Graphics Forum (Proc. SGP) 27, 5 (2008), 1459-1468. – reference: Li H., Adams B., Guibas L. J., Pauly M.: Robust single-view geometry and motion reconstruction. ACM Transactions Graphics (Proc. SIGGRAPH Asia) (2009). – reference: Rivers A., James D.: Fastlsm: Fast lattice shape matching for robust real-time deformation. ACM Transactions on Graphics (Proc. SIGGRAPH) 26, 3 (2007), 82-1-82-6. – reference: Allen B., Curless B., Popovic Z.: Articulated body deformation from range scan data. ACM Transactions on Graphics 21, 3 (2002), 612-619. – reference: Horn B., Hilden H., Negahdaripour S.: Closed-form solution of absolute orientation using orthonormal matrices. Journal of the Optical Society of America 5 (1988), 1127-1135. – reference: Xu W., Wang J., Yin K., Zhou K., Van De Panne N., Chen F., Guo B.: Joint-aware manipulation of deformable models. ACM Transactions on Graphics (Proc. SIGGRAPH) 28, 3 (2009), 35-1-35-9. – reference: Shen D.: Image registration by local histogram matching. Pattern Recognition 40, 4 (2007), 1161-1172. – reference: Zitová B., Flusser J.: Image registration methods: a survey. Image Vision Computer 21, 11 (2003), 977-1000. – reference: Teran J., Sifakis E., Blemker S., Hing V. N. T., Lau C., Fedkiw R.: Creating and simulating skeletal muscle from the visible human data set. IEEE TVCG 11 (2005), 317-328. – reference: Sueda S., Kaufman A., Pai D.: Musculotendon simulation for hand animation. ACM Transactions on Graphics (Proc. SIGGRAPH'08), 27, 3 (2008), 83-1-83-8. – reference: Schaefer S., McPhail T., Warren J.: Image deformation using moving least squares. ACM Transactions on Graphics (Proc. SIGGRAPH) 25, 3 (2006), 533-540. – reference: Sumner R. W., Schmid J., Pauly M.: Embedded deformation for shape manipulation. ACM Transactions on Graphics (Proc. SIGGRAPH), 26, 3 (2007), 80-2-80-7. – reference: Herda L., Urtasun R., Fua P.: Hierarchical implicit surface joint limits for human body tracking. Computer Vision and Image Understanding 99, 2 (2005), 189-209. – reference: Vlasic D., Baran I., Matusik W., Popovic J.: Articulated mesh animation from multi-view silhouettes. ACM Transactions on Graphics 27, 3 (2008), 97:1-97:9. – reference: Weinstein R., Teran J., Fedkiw R.: Dynamic simulation of articulated rigid bodies with contact and collision. IEEE TVCG 12 (2006), 365-374. – reference: Jollife T.: Principle Component Analysis. Springer-Verlag, New York (1986). – reference: Faure F.: Fast iterative refinement of articulated solid dynamics. IEEE TVCG 5, 3 (1999), 268-276. – reference: Anguelov D., Srinivasan P., Koller D., Thrun S., Rodgers J., Davis. J.: Scape: Shape completion and animation of people. ACM Transactions on Graphics (Proc. SIGGRAPH) (2005). – reference: Mirtich B., Canny J.: Impulse-based dynamic simulation. The Algorithmic Foundations of Robotics (1994). – reference: Bronstein A., Bronstein M., Kimmel R.: Topology-invariant similarity of nonrigid shapes. International Journal of Computer Vision 81, 3 (2009), 281-301. – reference: Lipman Y., Funkhouser T.: Mobius voting for surface correspondence. ACM Transactions on Graphics (Proc. SIGGRAPH) 28, 3 (2009). – reference: Zhang H., Sheffer A., Cohen-Or D., Zhou Q., Van Kaick O., Tagliasacchi A.: Deformation-driven shape correspondence. Computer Graphics Forum (Proc. SGP) 27, 5 (2008), 1431-1439. – reference: Besl P., McKay N.: A method for registration of 3-d shapes. IEEE Transactions on PAMI 14, 2 (1992), 239-256. – reference: Sebastian T., Tek H., Crisco J., Wolfe S., Kimia B.: Segmentation of carpal bones from ct images using skeletally coupled deformable models. Medical Image Analysis 7, 1 (2003), 21-45. – reference: Müller M., Heidelberger B., Teschner M., Gross M.: Meshless deformations based on shape matching. ACM Transactions on Graphics (Proc. SIGGRAPH) (2005), 471-478. – reference: Huang Q., Adams B., Wicke M., Guibas L.: Non-rigid registration under isometric deformations. Computer Graphics Forum 27, 5 (2008), 1449-1457. – reference: Papademetris X., Dione D., Dobrucki L., Staib L., Sinusas A.: Articulated rigid registration for serial lower-limb mouse imaging. Proc. MICCAI 3750 (2005), 919-926. – reference: Charpiat G., Maurel P., Pons J., Keriven R., Faugeras O.: Generalized gradients: Priors on minimization flows. International Journal of Computer Vision 73, 3 (2007), 325-344. – reference: Moore M., Wilhelms J.: Collision detection and response for computer animation. Proc. SIGGRAPH 22, 4 (1988), 289-298. – reference: Audette M., Ferrie F., Peters T.: An algorithmic overview of surface registration techniques for medical imaging. Medical Image Analysis 4, 3 (2000), 201-217. – year: 1994 article-title: Impulse‐based dynamic simulation publication-title: The Algorithmic Foundations of Robotics – volume: 21 start-page: 977 issue: 11 year: 2003 end-page: 1000 article-title: Image registration methods: a survey publication-title: Image Vision Computer – volume: 27 start-page: 1459 issue: 5 year: 2008 end-page: 1468 article-title: Automatic registration for articulated shapes publication-title: Computer Graphics Forum (Proc. 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| SubjectTerms | Algorithms Bones Computer animation Computer Science Displacement Elastic deformation I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling, Physically Based Modeling; I.4.8 [Image Processing and Computer Vision]: Scene Analysis, Surface fitting I.4.8 [Image Processing and Computer Vision]: Scene Analysis Mathematical models Medical Medical imaging Modeling and Simulation musculoskeletal system Optimization algorithms Parametrization Physically Based Modeling Skeletal system Studies Surface fitting template registration |
| Title | Creating and Animating Subject-Specific Anatomical Models |
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