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High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions
November/December 2007 (vol. 13 no. 6)
pp. 1696-1703
Surgical approaches tailored to an individual patient's anatomy and pathology have become standard in neurosurgery. Precise preoperative planning of these procedures, however, is necessary to achieve an optimal therapeutic effect. Therefore, multiple radiological imaging modalities are used prior to surgery to delineate the patient's anatomy, neurological function, and metabolic processes. Developing a three-dimensional perception of the surgical approach, however, is traditionally still done by mentally fusing multiple modalities. Concurrent 3D visualization of these datasets can, therefore, improve the planning process significantly. In this paper we introduce an application for planning of individual neurosurgical approaches with high-quality interactive multimodal volume rendering. The application consists of three main modules which allow to (1) plan the optimal skin incision and opening of the skull tailored to the underlying pathology; (2) visualize superficial brain anatomy, function and metabolism; and (3) plan the patient-specific approach for surgery of deep-seated lesions. The visualization is based on direct multi-volume raycasting on graphics hardware, where multiple volumes from different modalities can be displayed concurrently at interactive frame rates. Graphics memory limitations are avoided by performing raycasting on bricked volumes. For preprocessing tasks such as registration or segmentation, the visualization modules are integrated into a larger framework, thus supporting the entire workflow of preoperative planning.

[1] M. Atkins, K. Siu, B. Law, J. Orchard, and W. Rosenbaum, Difficulties of T1 Brain MRI Segmentation Techniques. In Proc. of SPIE Med. Imaging, volume 4684, pages 1837–1844, 2002.
[2] J. Beyer, M. Hadwiger, S. Wolfsberger, C. Rezk-Salama, and K. Bühler, Segmentierungsfreie Visualisierung des Gehirns für Direktes Volume Rendering. In Proc. of Bildverarb. für die Medizin, pages 333–337, 2007.
[3] W. Cai and G. Sakas, Data Intermixing and Multi-Volume Rendering. In Proc. of Eurographics, pages 359–368, 1999.
[4] M. Capek, L. Mroz, and R. Wegenkittl, Robust and Fast Medical Registration of 3D-Multi-Modality Data Sets. In Proc. of Medicon, pages 515–518, 2001.
[5] S. DiMaio, N. Archip, N. Hata, I. F. Talos, S. K. Warfield, A. Majumdar, N. McDannold, K. Hynynen, P. R. Morrison, W. M. Wells, D. F. Kacher, R. Ellis, A. J. Golby, P. M. Black, F. A. Jolesz, and R. Kikinis, Image-guided Neurosurgery at Brigham and Women's Hospital: The Integration of Imaging, Navigation and Interventional Devices. IEEE Engineering in Medicine and Biology Magazine, 25 (5): 67–73, 2006.
[6] P. Felkel, R. Wegenkittl, and M. Bruckschwaiger, Implementation and Complexity of the Watershed-from-Markers Algorithm Computed as a Minimal Cost Forrest. In Proc. of Eurographics, pages 26–35, 2001.
[7] M. Ferré, A. Puig, and D. Tost, A Framework for Fusion Methods and Rendering Techniques of Multimodal Volume Data. Computer Animation and Virtual Worlds, 15: 63–77, 2004.
[8] A. Ghosh, P. Prabhu, A. E. Kaufman, and K. Mueller, Hardware Assisted Multichannel Volume Rendering. In Proc. of Computer Graphics International, pages 2–7, 2003.
[9] M. Hadwiger, C. Berger, and H. Hauser, High-Quality Two-Level Volume Rendering of Segmented Data Sets on Consumer Graphics Hardware. In Proc. of IEEE Visualization, pages 301–308, 2003.
[10] M. Hadwiger, C. Sigg, H. Scharsach, K. Buhler, and M. Gross, Real-Time Ray-Casting and Advanced Shading of Discrete Isosurfaces. In Proc. of Eurographics, pages 303–312, 2005.
[11] P. Jannin, O. Fleig, E. Seigneuret, C. Grova, X. Morandi, and J. Scarabin, Multimodal and Multi-Informational Neuro-Navigation. In Proc. of CARS - Computer Assisted Radiology and Surgery, pages 167–172, 2000.
[12] J. Kniss, G. Kindlmann, and C. Hansen, Multidimensional Transfer Functions for Interactive Volume Rendering. IEEE Transactions on Visualization and Computer Graphics, 8 (3): 270–285, 2002.
[13] J. Krüger and R. Westermann, Acceleration Techniques for GPU-based Volume Rendering. In Proc. of IEEE Visualization, pages 287–292, 2003.
[14] I. H. Manssour, S. S. Furuie, S. D. Olabarriaga, and C. M. Freitas, Visualizing Inner Structures in Multimodal Volume Data. In Proc. of SIB-GRAPI, pages 51–58, 2002.
[15] R. Mullick, R. N. Bryan, and J. Butman, Confocal Volume Rendering: Fast Segmentation-Free Visualization of Internal Structures. In Proc. of SPIE - Int. Symp. on Optical Science and Technology, 2000.
[16] A. Neubauer, S. Wolfsberger, M. Forster, L. Mroz, R. Wegenkittl, and K. Bühler, STEPS - An Application for Simulation of Transsphenoidal Endonasal Pituitary Surgery. In Proc. of IEEE Visualization, pages 513–520, 2004.
[17] C. Rezk-Salama, K. Engel, M. Bauer, G. Greiner, and T. Ertl, Interactive Volume Rendering on Standard PC Graphics Hardware Using Multi-Textures and Multi-Stage Rasterization. In Proc. of Graphics Hardware, pages 109–118, 2000.
[18] C. Rezk-Salama and A. Kolb, Opacity Peeling for Direct Volume Rendering. In Proc. of Eurographics, pages 597–606, 2006.
[19] F. Rößler, E. Tejada, T. Fangmeier, T. Ertl, and M. Knauff, GPU-based Multi-Volume Rendering for the Visualization of Functional Brain Images. In Proc. of SimVis, pages 305–318, 2006.
[20] H. Scharsach, M. Hadwiger, A. Neubauer, S. Wolfsberger, and K. Bühler, Perspective Isosurface and Direct Volume Rendering for Virtual Endoscopy Applications. In Proc. of Eurovis '06, pages 315–323, 2006.
[21] L. Serra, R. A. Kockro, C. G. Guan, N. Hern, E. C. K. Lee, Y. H. Lee, C. Chan, and W. L. Nowinski, Multimodal Volume-based Tumor Neuro-surgery Planning in the Virtual Workbench. In Proc. of MICCAI, pages 1007–1015, 1998.
[22] T. Song, E. Angelini, B. Mensh, and A. Laine, Comparison Study of Clinical 3D MRI Brain Segmentation Evaluation. In Proc. of IEEE Engineering in Medicine and Biology Society, pages 1671–1674, 2004.
[23] U. Tiede, T. Schiemann, and K. H. Höhne, High Quality Rendering of Attributed Volume Data. In Proc. of IEEE Visualization, pages 255–262, 1998.
[24] F. Vega Higuera, P. Hastreiter, R. Naraghi, R. Fahlbusch, and G. Greiner, Smooth Volume Rendering of Labeled Medical Data on Consumer Graphics Hardware. In Proc. of SPIE Med. Imaging, pages 13–21, 2005.
[25] D. Weiskopf, K. Engel, and T. Ertl, Interactive Clipping Techniques for Texture-Based Volume Visualization and Volume Shading. IEEE Transactions on Visualization and Computer Graphics, 9 (3): 298–312, 2003.
[26] R. Westermann and T. Ertl, Efficiently Using Graphics Hardware in Volume Rendering Applications. In Proc. of SIGGRAPH, pages 169–178, 1998.
[27] L. Williams, Casting Curved Shadows on Curved Surfaces. In Proc. of SIGGRAPH, pages 270–274, 1978.
[28] B. Wilson, E. B. Lum, and K. Ma, Interactive Multi-Volume Visualization. In Proc. of Int. Conf. on Comp. Science, pages 102–110, 2002.

Index Terms:
Multimodal Volume Rendering, Hardware Assisted Raycasting, Surgery Planning
Citation:
Johanna Beyer, Markus Hadwiger, Stefan Wolfsberger, Katja Bühler, "High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1696-1703, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70560
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