Towards an identification of tumor growth parameters from time series of images

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

Volumn 4791 LNCS, Issue PART 1, 2007, Pages 549-556

  Konukoglu, Ender ^a   Clatz, Olivier ^a,c   Bondiau, Pierre Yves ^b   Sermesant, Maxime ^a   Delingette, Hervé ^a   Ayache, Nicholas ^a  

^a INRIA   (France)

^b CENTRE ANTOINE LACASSAGNE   (France)

^c SPL Harvard   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; INVERSE PROBLEMS; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; TIME SERIES ANALYSIS; TUMORS;

FAST MARCHING METHOD; REACTION-DIFFUSION FORMALISM;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; BRAIN TUMOR; CANCER INVASION; CANCER STAGING; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; GLIOBLASTOMA; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; BRAIN NEOPLASMS; GLIOBLASTOMA; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; NEOPLASM INVASIVENESS; NEOPLASM STAGING; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 79953221924     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75757-3_67     Document Type: Conference Paper

References (14)

1. Tovi, M.: Mr imaging in cerebral gliomas analysis of tumour tissue components, Acta Radiol. Suppl. (1993)
2. Kantor, G., Loiseau, H., Vital, A., Mazeron, J.: Descriptions of gtv and ctv for radiation therapy of adult glioma. Cancer Radiother (2001)
3. Giese, A., Kluwe, L., Laube, B., Meissner, H., Berens, M., Westphal, M.: Migration of human glioma cells on myelin. Neurosurgery 38(4) (1996)
4. Swanson, K., Alvord, E., Murray, J.: Virtual brain tumours (gliomas) enhance the reality of medical imaging and highlight inadequacies of current therapy. British Journal of Cancer 86 (2002)
5. Clatz, O., Sermesant, M., Bondiau, P., Delingette, H., Warfield, S., Malandain, G., Ayache, N.: Realistic simulation of the 3d growth of brain tumors in mr images coupling diffusion with biomechanical deformation. IEEE T.M.I. 24(10) (2005)
6. Jbabdi, S., Mandonnet, E., Duffau, H., Capelle, L., Swanson, K., Pélégrini-Issac, M., Guillevin, R., Benali, H.: Simulation of anisotropic growth of low-grade gliomas using diffusion tensor imaging. Magnetic Reson. in Med. 54 (2005)
7. Murray, J.: Mathematical Biology. Springer, Heidelberg (2002)
8. Konukoglu, E., Sermesant, M., Clatz, O., Peyrat, J.M., Delingette, H., Ayache, N.: A recursive anisotropic fast marching approach to reaction diffusion equation: Application to tumor growth modeling. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol. 4584, Springer, Heidelberg (2007)
9. Aronson, D., Weinberger, H,: Multidimensional nonlinear diffusion arising in population genetics, Advances in Mathematics 30 (1978)
10. Keener, J., Sneyd, J.: Mathematical physiology. Springer, Heidelberg (1998)
11. Sethian, J,: Level set methods and fast marching methods: Evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science. Cambridge University Press, Cambridge (1999)
12. Sethian, J., Vladimirsky, A.: Ordered upwind methods for static hamilton-jacobi equations: theory and algorithms. SIAM J. Numer. Anal. 41 (2003)
13. Powell, M.: Uobyqa: unconstrained optimization by quadratic approximation. Math. Program. Ser. B 92 (2002)
14. Alexander, D., Pierpaoli, C., Basser, P., Gee, J.: Spatial transformations of diffusion tensor magnetic: resonance images. IEEE Trans. Med. Imag. 20 (2001)