[en] Our goal is to fuse multimodality imagery to enhance image-guided neurosurgery. Images that need to be fused must be registered. Registration becomes a challenge when the imaged object deforms between the times the images to be fused are taken. This is the case when “brain-shift” occurs. We begin by describing our strategy for nonrigid registration via finite-element methods. Then, we independently discuss an image fusion strategy based on a model of the human visual system. We illustrate the operation of many components of the registration system and the operation of the fusion system.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others Mechanical engineering
Author, co-author :
Verly, Jacques ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images
Vigneron, Lara; Université de Liège - ULiège > Dept. of Electrical Engineering and Computer Science
Petitjean, Nicolas; Université de Liège - ULiège > Dept. of Electrical Engineering and Computer Science
Martin, Christophe; Université de Liège - ULiège > Dept. of Electrical Engineering and Computer Science
Guran, Raluca; Université de Liège - ULiège > Dept. of Electrical Engineering and Computer Science
Boman, Romain ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > LTAS-Mécanique numérique non linéaire
Robe, Pierre; Université de Liège - ULiège > CHU > Dept. of Neurosurgery
Language :
English
Title :
Human-Visual-System-Based Fusion of Multimodality 3D Neuroimagery using Brain-Shift-Compensating Finite-Element-Based Deformable Models
Publication date :
February 2003
Event name :
SPIE Conference on Visualization, Image-guided Procedures and Display
Event place :
San Diego, United States - California
Event date :
15-20 February 2003
Audience :
International
Journal title :
Proceedings of SPIE: The International Society for Optical Engineering
ISSN :
0277-786X
eISSN :
1996-756X
Publisher :
International Society for Optical Engineering, Bellingham, United States - Washington
Special issue title :
Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display
M. A. Audette and T. M. Peters, "Level-set surface segmentation and registration for computing intrasurgical deformations," in Medical Imaging: Image Processing, K. M. Hanson, ed., Proc. SPIE 3661, pp. 110-121, 1999.
M. Ferrant, Physics-based Deformable Modeling of Volumes and Surfaces for Medical Image Registration, Segmentation and Visualization. PhD thesis, Université catholique of Louvain, Telecommunications Laboratory, Louvain-la-Neuve, Belgium, April 2001.
M. Ferrant, A. Nabavi, B. Macq, F. A. Jolesz, R. Kikinis, and S. K. Warfield, "Registration of 3D intraoperative MR images of the brain using a finite element biomechanical model," IEEE Trans. Medical Imaging 20(12), pp. 1384-1397, Dec. 2001.
J. V. Hajnal, D. L. G. Hill, and D. J. Hawkes, Medical Image Registration, The Biomedical Engineering Series, CRC Press, Boca Raton, FL, 2001.
R. Whitaker, "A level-set approach to 3D reconstruction from range data," International Journal of Computer Vision 29(3), pp. 203-231, 1998.
D. Adalsteinsson and J. A. Sethian, "A fast level set method for propagating interfaces," J. Computational Physics 118, pp. 269-277, 1995.
P. E. Danielsson, "Euclidean distance mapping," Computer Graphics and Image Processing 14(3), pp. 227-248, 1980.
P. J. Besl and N. D. McKay, "A method for registration of 3D shapes," IEEE Trans. Pattern Analysis and Machine Intelligence 14(2), pp. 239-256, 1992.
S. Lavallée and R. Szeliski, "Recovering the position and orientation of free-form objects from image contours using 3D distance maps," IEEE Trans. Pattern Analysis & Machine Intelligence 17(2), pp. 378-390, 1995.
O. C. Zienkiewicz and R. L. Taylor, The Finite Element Method, vol. 1: The Basis, Butterworth-Heinemann, Oxford, NJ, 5th ed., UK.
W. Schroeder, K. Martin, and B. Lorensen, The Visualization Toolkit: An Object Oriented Approach to 3D Graphics, Prentice Hall PTR, Upper Saddle River, NJ, 2nd ed., 1998.
B. Geiger, "Three-dimensional modelling of human organs and its application to diagnosis and surgical planning," Tech. Rep. 2105, INRIA, Sophia-Antipolis, France, 1993.
G. M. Treece, R. W. Prager, and A. H. Gee, "Regularized marching tetrahedra: improved isosurface extraction," tech. rep., Cambridge University, Engineering Department, Cambridge, UK, 1998.
C. F. Ollivier-Gooch, Grummp Version 0.2.1 User's Guide. University of British Columbia, Dept. of Mechanical Engineering, Vancouver, BC, Canada, 2002.
J. R. Shewchuck, Delaunay refinement mesh generation. PhD thesis, Carnegie Mellon University, School of Computer Science, Pittsburgh, PA, 1997.
M. I. Miga, K. D. Paulsen, P. J. Hoopes, F. E. Kennedy, A. Hartov, and D. W. Roberts, "In-vivo quantification of a homogeneous brain deformation model for updating preoperative images during surgery," IEEE Trans. Biomedical Engineering 47(2), pp. 266-273, Feb. 2000.
Samtech SA, Liège, Belgium, SAMCEF User Manual -9.1, v9.1 ed., 2002-2003.
W. Ross, A. Waxman, W. Streilein, J. Verly, F. Liu, M. Braun, P. Harmon, and S. Rak, "Multi-sensor 3D image fusion and interactive search," in Proc. of the 3rd International Conference on Information Fusion (Fusion 2000), 2000.
D. A. Fay, J. G. Verly, M. I. Braun, C. Frost, J. P. Racamato, and A. M. Waxman, "Fusion of multi-sensor passive and active 3D imagery," in Enhanced and Synthetic Vision 2001, J. G. Verly, ed., Proc. SPIE 4363, pp. 219-230, April 2001.
A. Waxman, J. Verly, D. Fay, F. Liu, M. Braum, B. Pugliese, W. Ross, and W. Streilein, "A prototype system for 3D color fusion and mining of multisensor/spectral imagery," in Proc. of the 4th International Conference on Information Fusion (Fusion 2001), I, pp. WeC1-3-WeC1-10, International Society of Information Fusion, (Sunnyvale, CA), August 2001.
M. Aguilar and A. L. Garrett, "Neurophysiologically-motivated sensor fusion for visualization and characterization of medical imagery," in Proc. of the 4th International Conference on Information Fusion (Fusion 2001), I, pp. WeC3-11-WeC3-18, International Society of Information Fusion, (Sunnyvale, CA), August 2001.
M. Aguilar and A. L. Garrett, "Biologically-based sensor fusion for medical imaging," in Sensor Fusion: Architectures, Algorithms and Applications V, Proc. SPIE 4385, pp. 149-159, April 2001.
M. Aguilar and J. New, "Fusion of multi-modality volumetric medical imagery," in Proc. of the 5th International Conference on Information Fusion (Fusion 2002), International Society of Information Fusion, (Sunnyvale, CA), 2002.
S. Grossberg, ed., Neural Networks and Natural Intelligence, The MIT Press, Cambridge, MA, 1988.
