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Research on the Key Technology of Image Guided Surgery

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Warianty tytułu
PL
Badania możliwości technologii sterowanej obrazem operacji medycznej
Języki publikacji
EN
Abstrakty
EN
It research on the key technology on IGS (image-guided surgery). It proposes medical image segmentation based on PCNN and the virtual endoscopic scenes real-time rendering method based on GPU parallel computing technology, which improves the display quality of IGS’s virtual scene and real-time rendering speed. These methods are very important for IGS’s applications.
PL
Przedstawiono technologię operacji bazującej na prowadzonym systemie obrazu IGS. Zaproponowano segmentację obrazu I możliwość otrzymywania obrazu endoskopowego w trybie czasu rzeczywistego.
Rocznik
Strony
29--33
Opis fizyczny
Bibliogr. 20 poz., il., schem., tab.
Twórcy
autor
autor
autor
autor
Bibliografia
  • [1] A D Nijmeh, etal. Image guided navigation in oral and maxillofacial surgery [j]. British Journal of Oral and Maxillofacial Surgery. 2005, 43(4): 294-302.
  • [2] Luo Xiping,Tian Jie, Lin Yao. An algorithm for Segmentation of Medical Image Series Based on Active Contour Model. Journal of Software. 2002, 13(6): 1050-1058.
  • [3] Luo Xiping,Tian Jie, Lin Yao. An algorithm for Segmentation of Medical Image Series Based on Active Contour Model. Journal of Software. 2002, 13(6):1050-1058.
  • [4] Ma Yide,Dai Rolan,Li Lian,et al. Image segmentation of embryonic plant cell using pulse-coupled neural networks[J]. Chinese Science Bulletion, 2002,47(02):167-172.
  • [5] Ma Yide, Dai Rolan, Li Lian, et al. The State and Development of Cell Image Segmentation Technology. Journal of Biomedical Engineering. 2002,19(3):487-492.
  • [6] Eckhorn R, Reitboeck H J, Arndt M, Dicke P. Feature linking via synchronization among distributed assemblies: simulation of results from cat cortex. Neural Computation, 1990, 2(3), 293-307.
  • [7] Robert S. The Tsallis entropy of natural information[J]. Physica A: Statistical Mechanics and Its Applications, 2007, 386(1):101-118.
  • [8] Tsallis C, Plastino A R, Zheng W M. Power-law sensitivity to initial conditions-new entropic representation[J]. Chaos Solitons and Fractals. 1997, 8(6):885-891.
  • [9] Eckhorn R,Frien A, Bauer R, et al. . High frequency oscillations in primary visual cortex of awake monkey. NeuroReport, 1993, 4(3):243-246.
  • [10] Johnson L J, Padgett M L. PCNN models and applications. IEEE Transactions on Neural Networks, 1999, 10(3):480-498.
  • [11] Stewart R D, Fermin I,Opper M. Region growing with pulsecoupled neural networks: An alternative to seeded region growing[J]. IEEE Transaction on Neural Networks, 2002, 13(6): 1557-1562.
  • [12] Xiaodong Gu. A New Approach to Image Authentication Using Local Image Icon of Unit-linking PCNN. The 2006 IEEE International Joint Conference on Neural Network. 2006,2:1036-1041.
  • [13] Jiuwen Zhang,Kun Zhan, Yide Ma. Rotation and Scale Invariant Antinoise PCNN Features for Content-based Image Retrieval. 2007,17(2):121-132.
  • [14] Yide Ma, Zhaobin Wang,Chenhu Wu. Feature Extraction from Noisy Image Using PCNN. 2006 International Conference on Information Acquisition(ICIA 2006). 2006, 2:808-813;
  • [15] Zhang Yudong, Wu Lenan. Image Segmentation Based on 2D Tsallis Entropy with Improved Pulse Coupled neural Networks. Journal of Southeast University. 2008, 38(4):579-584.
  • [16] Kaufman A , Mueller K1 Volume visualization and volume graphics [R]1 Stony Brook , NY: Stony Brook University , 2003.
  • [17] Jens Krüger, Rüdiger Westermann. Linear algebra operators or GPU implementation of numerical algorithms[J]. ACM Trans Graph. 2003, 22(3):908-916.
  • [18] Scharsach H. Advanced GPU raycasting [C]. Proceedings of Central European Seminar on Computer Graphics 2005, Budmerice Castle, 2005:69-76.
  • [19] Shi Weili, Miao Yu, Chen Zhanfang, Zhang Hongbiao. Research of Automatic Medical Image Segmentation Algorithm Based on Tsallis Entropy and Improved PCNN. Proceedings of the IEEE International Conference on Mechatronics and Automation.2009:1004-1008.
  • [20] Shi Weili,MIoa Yu, etc. Real-time Rendering Algorithm for Virtual Endoscopy Based on GPU.ICEEE2010. 2010, No.5, 3356-2259.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOH-0062-0008
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