The Virtual Endoscope of Neurosurgery Used for Transnasal Approach

Article Preview

Abstract:

This paper presents and implements an automatic roaming and fast virtual endoscopic neurosurgery system for transsexual approach, which can be compatible with the fiber-optic endoscopic transnasal approach in the skull base surgery, and accurately locate the position and their mutual relations among the lesions, tumors and surrounding vital anatomical structures. The system uses a multithreaded RayCasting volume-rendering algorithm based on the graphics processor (GPU). It reconstructs the nasal three-dimensional structure in the skull base surgery, and optimizes the centerline extraction that can be carried out automatically. In real-time display, it improves the translucent rendering optical model, taking into account lighting model important parameter - the image gradient translucent degree of non-linear effects, and can fully display the skull surface and internal implied the interface and internal details.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1282-1288

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Fukushima, T., et al., Ventriculofiberscope: a new technique for endoscopic diagnosis and operation. Journal of neurosurgery, 1973. 38 (2): pp.251-256.

DOI: 10.3171/jns.1973.38.2.0251

Google Scholar

[2] Fujikura, T., et al., Clinical application of virtual endoscopy as a support system for endoscopic sinus surgery. Acta oto-laryngologica, 2009. 129 (6): pp.674-680.

DOI: 10.1080/00016480802360640

Google Scholar

[3] Wolfsberger, S., et al., Advanced virtual endoscopy to endoscopic transsphenoidal pituitary surgery. Neurosurgery, 2006. 59 (5): p.1001.

DOI: 10.1227/01.neu.0000245594.61828.41

Google Scholar

[4] Vining, DJ and Others, Virtual colonoscopy. Gastrointestinal endoscopy clinics of North America, 1997. 7 (2): p.285.

DOI: 10.1016/s1052-5157(18)30313-1

Google Scholar

[5] Richard, A., Virtual endoscopy: evaluation using the visible human datasets and comparison with real endoscopy in patients. Medicine meets virtual reality: global healthcare grid, 1997. 39: p.195.

Google Scholar

[6] Kennedy, DW, Functional endoscopic sinus surgery: technique. Archives of Otolaryngology-Head and Neck Surgery, 1985. 111 (10): p.643.

DOI: 10.1001/archotol.1985.00800120037003

Google Scholar

[7] Sahoo, PK, S. Soltani and A. Wong, A survey of thresholding techniques. Computer vision, graphics, and image processing, 1988. 41 (2): pp.233-260.

DOI: 10.1016/0734-189x(88)90022-9

Google Scholar

[8] FMRIB Software Library, http: /www. fmrib. ox. ac. uk/fsl/fsl/list. html.

Google Scholar

[9] Yao Demin and SONG Zhi-Jian, virtual endoscopy key technology research and clinical applications. Biomedical Engineering, 2008. 25 (001): 18 - 22.

Google Scholar

[10] Deschamps, T. and LD Cohen, Fast extraction of minimal paths in 3D images and applications to virtual endoscopy1. Medical Image Analysis, 2001. 5 (4): pp.281-299.

DOI: 10.1016/s1361-8415(01)00046-9

Google Scholar

[11] Levoy, M., Display of surfaces from volume data. Computer Graphics and Applications, IEEE, 1988. 8 (3): pp.29-37.

DOI: 10.1109/38.511

Google Scholar

[12] Borgefors, G., Distance transformations in digital images. Computer vision, graphics, and image processing, 1986. 34 (3): pp.344-371.

DOI: 10.1016/s0734-189x(86)80047-0

Google Scholar

[13] Roth, SD, Ray casting for modeling solids. Computer Graphics and Image Processing, 1982. 18 (2): pp.109-144.

DOI: 10.1016/0146-664x(82)90169-1

Google Scholar

[14] Levoy, M., Efficient ray tracing of volume data. ACM Transactions on Graphics (TOG), 1990. 9 (3): pp.245-261.

DOI: 10.1145/78964.78965

Google Scholar

[15] Cook, RL and KE Torrance, A reflectance model for computer graphics. ACM Transactions on Graphics (TOG), 1982. 1 (1): pp.7-24.

DOI: 10.1145/357290.357293

Google Scholar

[16] Hohne, KH and R. Bernstein, Shading 3D-images from CT using gray-level gradients. Medical Imaging, IEEE Transactions on, 1986. 5 (1): pp.45-47.

DOI: 10.1109/tmi.1986.4307738

Google Scholar