Deformable structures localization and reconstruction in 3D images

VISAPP 2007 - 2nd International Conference on Computer Vision Theory and Applications, Proceedings

Volumn SP, Issue , 2007, Pages 215-222

  Moroni, Davide ^a   Colantonio, Sara ^a   Salvetti, Ovidio ^a   Salvetti, Mario ^b  

^a ISTI CNR   (Italy)

^b UNIVERSITY OF PISA   (Italy)

Author keywords

Artificial neural networks; Cardiac MRI; Deformable structures; Image segmentation

Indexed keywords

3-D IMAGE; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; AUTOMATIC IDENTIFICATION; CARDIAC MRI; DEFORMABLE STRUCTURES; IMAGE SEQUENCE; IMAGING APPLICATIONS; LEFT VENTRICLES; MRI SEQUENCES; PROCESSING STAGE; TWO-STAGE METHODS;

AUTOMATION; BACKPROPAGATION; COMPUTER VISION; DEFORMATION; DIGITAL IMAGE STORAGE; ELECTRONIC DATA INTERCHANGE; FUZZY CLUSTERING; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; MEDICAL IMAGING; NEURAL NETWORKS; REMOTE SENSING; REPAIR;

THREE DIMENSIONAL;

EID: 45149090373     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. ACC\AHA Task Force (2005). ACC\AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult. Technical report, American College of Cardiology Foundation and the American Heart Association.
2. Bezdek, L. (1981). Pattern Recognition with Fuzzy Objective Function Algorithm. Plenum Press, New York.
3. Bregler, C. and Konig, Y. (1994). "Eigenlip" for robust speech recognition. In Acoustics, Speech, and Signal Processing ICASSP-94., volume II, pages 669-672.
4. Colantonio, S., Moroni, D., and Salvetti, 0. (2005). MRI left ventricle segmentation and reconstruction for the study of the heart dynamics. In IEEE ISSPIT, pages 213-218, Athens, Greece.
5. Colantonio, S., Moroni, D., and Salvetti, 0. (2006). Shape comparison and deformation analysis in biomedical applications. In Eurographics Italian Chapter Conference, pages 37-43.
6. Coppini, 0., Poli, R., and Valli, G. (1995). Recovery of the 3-D shape of the left ventricle from echocardiographic images. IEEE TMI, 14(2):301-317.
7. de Bruijne, M. and Nielsen, M. (2004). Image segmentation by shape particle filtering. ICPR, 03:722-725.
8. Declerck, J., Feldmar, J., Goris, M., and Betting, F. (1997). Automatic registration and alignment on a template of cardiac stress and rest reoriented SPECT images. IEEE Trans. Med. Imag., 16:727-737.
9. Di Bona, S., Niemann, H., Pieri, G., and Salvetti, 0. (2003). Brain volumes characterisation using hierarchical neural networks. Artificial Intelligence in Medicine, 28(3):307-322.
10. Di Bono, M., Pieri, G., and Salvetti, 0. (2004). A tool for system monitoring based on artificial neural networks. WSEAS Transactions on Systems, 3(2):746-751.
11. Faber, T., Stokely, E., Peshock, R., and Corbett, J. (1991). A model-based four-dimensional left ventricular surface detector. IEEE Tran. Med. Imag., 10:321-329.
12. Grenander, U. and Miller, M. I. (1998). Computational anatomy: an emerging discipline. Q. Appi. Math., LVI(4):617-694.
13. Huang, X., Metaxas, D., and Chen, T. (2004). Meta Morphs: Deformable shape and texture models. CVPR, 01:496-503.
14. Jolly, M., Duta, N., and Funka-Lea, 0. (2001). Segmentation of the left ventricle in cardiac MR images. In ICCV, pages 501-508.
15. Kass, M., Witkin, A., and Terzopulos, D. (1988). Snakes: Active contour models. IJCV, 1:321-331.
16. Kohonen, T. (1997). Self-Organizing Maps, volume 30 of Springer Series in Information Sciences. 2nd edition.
17. Mitchell, S., Bosch, J., Lelieveldt, B., van der Geest, R., Reiber, J., and Sonka, M. (2002). 3D active appearance models: Segmentation of cardiac MR and ultrasound images. IEEE TM, 21(9):1 1671178.
18. Moroni, D., Pemer, P., and Salvetti, 0. (2006). A general approach to shape characterization for biomedical problems. In Pemer, P., editor, Industrial Conference on Data Mining ICDM - Workshop on Mass-Data Analysis of Images and Signals, IBAI CD-Report, pages 56-65, Leipzig.
19. Papin, C., Bouthemy, P., Mèmin, E., and Rochard, G. (2000). Tracking and characterization of highly deformable cloud structures. In Computer Vision - ECCV 2000, volume 1843 of LNCS, pages 428-442. Springer Verlag.
20. Paragios, N. (2002). A variational approach for the segmantation of left ventricle in cardiac image analysis. IJCV, 50(3):345-362.
21. Paragios, N., Rousson, M., and Rainesh, V. (2002). Knowledge-based registration segmentation of the left ventricle: A level set approach. In Proc. Sixth IEEE Workshop on Application of Computer Vision, pages 37-42.
22. Riedmiller, M. and Braun, H. (1993). A direct adaptive method for faster backpropagation learning: The RPROP algorithm. In Proc. of the IEEE Intl. Conf on Neural Networks, pages 586-591, San Francisco, CA.
23. Stalidis, G., Maglaveras, N., Dimitriadis, A., and Pappas, C. (1999). Using learning classification and four- dimensional parametric modeling for the analysis of myocardial thickening. In Computers in Cardiology.
24. Üzümcü, M., Frangi, A., Sonka, M., Reiber, J., and Lclieveldt, B. (2003). ICA vs. PCA active appearance models: Application to cardiac MR segmentation. In LNCS, volume 2878, pages 451-458.