An improved 3D shape context based non-rigid registration method and its application to small animal skeletons registration

Computerized Medical Imaging and Graphics

Volumn 34, Issue 4, 2010, Pages 321-332

  Xiao, Di ^a   Zahra, David ^b   Bourgeat, Pierrick ^a   Berghofer, Paula ^b   Tamayo, Oscar Acosta ^a   Wimberley, Catriona ^b   Gregoire, Marie Claude ^b   Salvado, Olivier ^a  

^a CSIRO   (Australia)

^b AUSTRALIAN NUCLEAR SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

Author keywords

3D shape context; Micro CT images; Non rigid registration; Small animal skeleton registration

Indexed keywords

3-D SHAPE; GEODESIC DISTANCES; HIND LIMBS; MATCHING POINTS; MICRO CT; NONRIGID REGISTRATION; NONRIGID REGISTRATION METHOD; PRE-PROCESSING STEP; RAT HIND LIMB; SMALL ANIMAL; SMOOTHING METHODS; THIN-PLATE SPLINE MODELS; TOPOLOGICAL STRUCTURE; VERIFICATION METHOD;

ANIMALS; COMPUTERIZED TOMOGRAPHY; GEODESY; STRUCTURAL OPTIMIZATION; TOPOLOGY;

THREE DIMENSIONAL;

ANALYTICAL ERROR; ARTICLE; HINDLIMB; IMAGE PROCESSING; IMAGE QUALITY; IMAGE RECONSTRUCTION; METHODOLOGY; MICRO-COMPUTED TOMOGRAPHY; MOUSE; NONHUMAN; PRIORITY JOURNAL; RAT; SKELETON; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BONE AND BONES; HINDLIMB; IMAGING, THREE-DIMENSIONAL; MICE; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RATS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 77952236523     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2009.12.003     Document Type: Article

References (28)

1. Urschler M., Bischof H. Registering 3D lung surfaces using the shape context approach. Proceedings of the medical image understanding and analysis 2004, 212-215.
2. Belongie S., Malik J., Puzicha J. Matching Shapes. Proceedings of the eighth international conference on computer vision 2001, 454-461.
3. Belongie S., Malik J., Puzicha J. Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 2002, 24(24):509-522.
4. Mori G., Belongie S., Malik J. Shape contexts enable efficient retrieval of similar shapes. Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition, vol. 1 2001, I-723-I-730.
5. Mori G., Belongie S., Malik J. Efficient shape matching using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005, 27(11):1832-1837.
6. Carneiro G., Jepson A.D. Pruning local feature correspondences using shape context. Proceedings of the 17th conference on pattern recognition, vol. 3 2004, 16-19.
7. Yusuf M., Haider T. Recognition of handwritten Urdu digits using shape context. Proceedings of the 8th international multitopic conference 2004, 569-572.
8. Yusuf M., Haider T. Accelerated recognition of handwritten Urdu digits using shape context based gradual pruning. International Conference on Intelligent and Advanced Systems 2007, 601-604.
9. Liu X., Jia Y., Wang Y. An eigenvector approach based on shape context patterns for point matching. International symposium on communications and information technologies 2006, 455-458.
10. Yang F., Lu Y., Duan Y. Combining hierarchical segmentation and shape context based recognition. Proceedings of the 8th international conference on computer and information technology 2008, 839-844.
11. Nguyen T.-O., Tabbone S., Terrades O.R. Symbol descriptor based on shape context and vector model of information retrieval. The eighth IAPR international workshop on document analysis systems 2008, 191-197.
12. Singh L.B., Hazarika S.M. Enhanced shape context for object recognition. Proceedings of the international conference on advanced computing and communications 2007, 529-534.
13. Thayananthan A., Stenger B., Torr P.H.S., Cipolla R. Shape context and chamfer matching in cluttered scenes. Proceedings of the IEEE conference on computer vision and pattern recognition, vol. 1 2003, 127-133.
14. Mori G., Malik J. Estimating human body configurations using shape context matching. Proceedings of the European conference on computer vision, vol. 3 2002, 666-680.
15. Mori G., Malik J. Recovering 3D human body configurations using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 2006, 28:1052-1062.
16. Qui X., Wang Z., Xia S., Li J. Estimating articulated human pose from video using shape context. Proceedings of the fifth IEEE international symposium on signal processing and information technology 2005, 583-588.
17. Hao C., Qiu X., Wang Z., Chen S. Shape matching in pose reconstruction using shape context. Proceedings of the 12th international multi-media modelling conference 2006, 169-176.
18. Grundmann M., Meier F., Essa I. 3D shape context and distance transform for action recognition. Proceedings of the 19th international conference on pattern recognition 2008, 1-4.
19. Hsiao P., Chen C., Chang L. Human action recognition using temporal-state shape contexts. Proceedings of the 19th international conference on pattern recognition 2008, 1-4.
20. Kortgen M., Park G., Novotni M., Klein R. 3D shape matching with 3D shape context. Proceedings of the seventh central European seminar on computer graphics 2003.
21. Urschler M., Bauer J., Ditt H., Bischof H. SIFT and shape context for feature-based nonlinear registration of thoracic CT images. Proceedings of the computer vision approaches to medical image analysis 2006, 73-84.
22. Urschler M., Bischof H. Assessing breathing motion by shape matching of lung and diaphragm surfaces. Proceedings of the SPIE medical imaging, vol. 5746 2005, 440-452.
23. Xiao D., Bourgeat P.T., Fripp J.E., Tamayo O.A., Gregoire M., Salvado O. Non-rigid registration of small animal skeletons from micro-CT using 3D shape context. Proceedings of the SPIE, medical image 2009, 7259 2009, 72591G.
24. Giannarou S., Stathaki T. Object identification in complex scenes using shape context descriptor and multi-stage clustering. Proceedings of the 15th international conference on digital signal processing 2007, 244-247.
25. Jonker R., Volgenant A. A shortest augmenting path algorithm for dense and sparse linear assignment problems. Computing 1987, 38(4):325-340.
26. Bookstein F.L. Principal warps: thin-plate splines and the decomposition of deformation. IEEE Transactions on Pattern Analysis and Machine Intelligence 1989, 11(6):567-585.
27. Aspert N., Santa-Cruz D., Ebrahimi T. MESH: measuring errors between surfaces using the Hausdorff distance. Proceedings of the IEEE international conference on multimedia and expo (ICME), vol. I 2002, 705-708.
28. http://www.cs.unc.edu/~xushun/research/MeshValmet.html.