Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration

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

Volumn 2488, Issue , 2002, Pages 642-650

  Lorenzo Valdes M ^a   Sanchez Ortiz, G I ^a   Mohiaddin, R ^b   Rueckert, D ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ROYAL BROMPTON AND HAREFIELD NHS FOUNDATION TRUST   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DEFORMATION; HEART; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; MEDICAL IMAGING;

ATLAS-BASED SEGMENTATION; AUTOMATIC TRACKING; MANUAL SEGMENTATION; MOTION AND DEFORMATIONS; NONRIGID REGISTRATION; REGISTRATION ALGORITHMS; ROBUST PERFORMANCE; SEGMENTATION AND TRACKING;

IMAGE SEGMENTATION;

EID: 84974712427     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45786-0_79     Document Type: Conference Paper

References (19)

1. A. F. Frangi, W. J. Niessen, and M. A. Viergever. Three-dimensional modeling for functional analysis of cardiac images: A review. IEEE Transactions on Medical Imaging, 20(1):26-35, 2001.
2. J.P. Thirion and S. Benayoun. MyoTrack:A 3D deformation field method to measure cardiac motion from gated SPECT. In Medical Image Computing and Computer-Assisted Intervention, Lecture Notes in Computer Science, pages 697-706, Pittsburgh, USA, Oct 2000.
3. G.I. Sanchez-Ortiz, J. Declerck, J.A. Noble, and M. Mulet-Parada. Automating 3D Echocardiographic Image Analysis. In Medical Image Computing and Computer-Assisted Intervention, Lecture Notes in Computer Science, pages 687-696, Pittsburgh, USA, Oct 2000.
4. S. Plein, T.N. Bloomer, J.P. Ridgway, T.R. Jones, G.J. Bainbridge, and M.U. Sivananthan. Steady-state free precession magnetic resonance imaging of the heart: Comparison with segmented k-space gradient-echo imaging. Journal of Magnetic Resonance Imaging, 14(3):230-236, 2001.
5. J. S. Suri. Computer vision, pattern recognition and image processing in left ventricle segmentation: The last 50 years. Pattern Analysis and Applications, 3(3):209-242, 2002.
6. F. Vincent, P. Clarysse, P. Croiselle, and I. Magnin. Segmentation of the heart from MR image sequences using a 3D active model. Annals of Biomedical Engineering, 28(1):5-42, 2000.
7. B.P.F. Lelieveldt, R.J.Van der Geest, R.M. Ramze, J.G. Bosch, and J.H.C. Reiber. Anatomical model matching with fuzzy implicit surfaces for segmentation of thoracic volume scans. IEEE Transactions on Medica Imaging, 18(3):218-230, 1999.
8. T. F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. In Proc. 5th European Conference on Computer Vision (ECCV’98), volume 2, pages 484-498, 1998.
9. S.C. Mitchell, B.P.F. Lelieveldt, R.J.Van Der Geest, H. G. Bosch, J.H.C. Reiber, and M. Sonka. Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images. IEEE Transactions on Medical Imaging, 20:415-423, 2001.
10. S.C. Mitchell, B.P.F. Lelieveldt, J. G. Bosch, R.Van Der Geest, J.H.C. Reiber, and M. Sonka. Segmentation of cardiac MR volume data using 3D active appearance models. In SPIE Conference on Medical Imaging, Image Processing, page In press, 2002.
11. E. Bardinet, L. D. Cohen, and N. Ayache. Tracking and motion analysis of the left ventricle with deformable superquadratics. Medical Image Analysis, 1(2):129-149, 1996.
12. D. L. Collins, A. C. Evans, C. Holmes, and T. M. Peters. Automatic 3D segmentation of neuro-anatomical structures from MRI. InY. Bizais et al., editor, Information Processing in Medical Imaging, pages 139-152. Kluwer Academic Publishers, 1995.
13. J. M. Fitzpatrick, D. L. G. Hill, and C. R. Maurer,. Image registration. In Milan Sonka and J. Michael Fitzpatrick, editors, Handbook of Medical Imaging, volume 2, pages 447-513. SPIE Press, 2000.
14. D. Rueckert, L.I. Sonoda, C. Hayes, D.L.G. Hill, M.O. Leach, and D.J. Hawkes. Nonrigid registration using free-form deformations: Application to breast CT images. IEEE Transactions on Medical Imaging, 18(8):712-721, 1999.
15. C. R. Maurer, D. L. G. Hill, A. J. Martin, H. Liu, M. McCue, D. Rueckert, D. Lloret, W. A. Hall, R. E. Maxwell, D. J. Hawkes, and C. L. Truwit. Investigation of intraoperative brain deformation using a 1.5T interventional MR system: preliminary results. IEEE Transactions on Medical Imaging, 17(5):817-825, 1998.
16. C. Studholme, D.L.G. Hill, and D.J. Hawkes. Automated three-dimensional regisration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Medical Physics, 24(1):71-86, 1997.
17. A. F. Frangi, D. Rueckert, J. A. Schnabel, and W. J. Niessen. Automatic 3DASM construction via atlas-based landmarking and volumetric elastic registration. In Information Processing in Medical Imaging: Proc. 17th International Conference (IPMI’01), pages 78-91, Davis, CA, July 2001.
18. A. F. Frangi, D. Rueckert, J. A. Schnabel, and W. J. Niessen. Automatic construction of multiple-object three-dimensional statistical shape models: Application to cardiac modeling. IEEE Transactions on Medical Imaging, 2001. Submitted.
19. J.A. Schnabel, D. Rueckert, M. Quist, J.M. Blackall, A.D. Castellano-Smith, T. Hartkens, G.P. Penney, W.A. Hall, H. Liu, C.L. Truwit, F.A. Gerritsen, D.L.G. Hill, and D.J. Hawkes. A generic framework for non-rigid registration based on non-uniform multi-level free-form deformations. In Medical image computing and computed-assisted intervention - MICCAI, pages 573-581, 2001.