Automated interpretation of cardiac scintigrams

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2749, Issue , 2003, Pages 565-570

  Richter, Jens ^b   Ericsson, Anders ^a   Åström, Kalle ^a   Kahl, Fredrik ^a   Edenbrant, Lars ^c  

^a LUND INSTITUTE OF TECHNOLOGY   (Sweden)

^b Ideon Science Park   (Sweden)

^c LUND UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS;

3-D MODELING; ACTIVE SHAPE; AUTOMATED INTERPRETATION; AUTOMATED METHODS; AUTOMATIC SEGMENTATIONS; KEY FEATURE;

HEART;

EID: 35248869361     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45103-x_75     Document Type: Article

References (9)

1. A. Baumberg and Hogg D. Learning flexible models from image sequences. In Proc. European Conf. on Computer Vision, ECCV'94, pages 299-308, 1994.
2. A. Benayoun, Ayache N., and Cohen I. Adaptive meshes and nonrigid motion computation. In Proc. International Conference on Pattern Recognition, ICPR'94, 1994.
3. T.F. Cootes, A. Hill, C.J Taylor, and Haslam J. Use of active shape models for locating structure in medical images. IEEE Trans, medical imaging, 12(6):355-365, 1994.
4. T.F Cootes and C.J. Taylor. Statistical Models of Appearance for Computer Vision. University of Manchester, 2001.
5. Rhodri H. Davies, Tim F. Cootes, John C. Waterton, and Chris J. Taylor. An efficient method for constructing optimal statistical shape models. In Medical Image Computing and Computer-Assisted Intervention MICCAI'2001, pages 57-65, 2001.
6. Rhodri H. Davies, Carole J. Twining, Tim F. Cootes, John C. Waterton, and Chris J. Taylor. A minimum description length approach to statistical shape modeling. IEEE Trans, medical imaging, 21(5):525-537, 2002.
7. C. Kambhamettu and D.B. Goldgof. Points correspondences recovery in non-rigid motion. In Proc. Conf. Computer Vision and Pattern Recognition, CVPR '92, pages 222-237, 1992.
8. A. Kelemen, G. Szekely, and Gerig G. Elastic model-based segmentation of 3d neuroradiological data sets. IEEE Trans, medical imaging, 18(10):828-839, 1999.
9. Y. Wang, B.S. Peterson, and L.H Staib. Shape-based 3d surface correspondence using geodesics and local geometry. In Proc. Conf. Computer Vision and Pattern Recognition, CVPR'00, pages 644-651, 2000.