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Registration and Visualization of Medical Image Using Conditional Entropy and 3D Volume Rendering
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 Title & Authors
Registration and Visualization of Medical Image Using Conditional Entropy and 3D Volume Rendering
Kim, Sun-Worl; Cho, Wan-Hyun;
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 Abstract
Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we introduce a robust brain registration technique for correcting the difference between two temporal images by the different coordinate systems in MR and CT image obtained from the same patient. Two images are registered where this measure is minimized using a modified conditional entropy(MCE: Modified Conditional Entropy) computed from the joint histograms for the intensities of two given images, we conduct the rendering for visualization of 3D volume image.
 Keywords
Image registration;modified conditional entropy;rendering;
 Language
Korean
 Cited by
 References
1.
김경수, 이진학, 나종범 (2005). 정밀한 다중센서 영상정합을 위한 통계적 상관성의 증대기법, <전자공학회 논문지>, 42, 415-426

2.
김민석 (2003). VTK를 이용한 3차원 의료영상처리 시스템, 석사학위 논문, 단국대학교 대학원

3.
김영철 (2003). 의료영상의 3차원 가시화와 MRS 데이터를 이용한 종양의 추출, 석사학위 논문, 인제대학교 대학원

4.
이호, 홍헬렌, 신영길 (2005). 가우시안 가중치 거리지도를 이용한 PET-CT 뇌 영상정합, <소프트웨어 및 응용>, 32, 612-624

5.
조동욱, 김태우, 신승수, 김동원, 조태경 (2003). 마커 기반과 특징기반에 기초한 뇌 영상의 3차원 정합방법의 비교.고찰, <한국콘텐츠학회논문지>, 3, 85-97

6.
홍헬렌 (2005). 의료분야에서의 영상정합 연구, <정보과학회논문지>, 23, 61-67

7.
Cho, W. H., Kim, S. W., Lee, M. E., Kim, S. H., Park, S. Y. and Jeong, C. B. (2009). Multimodality im-age registration using spatial procrustes analysis and modified conditional entropy, Journal of Sigmal Processing Systems, 54, 101-114 crossref(new window)

8.
Kalender, W. A., Seissler, W., Klotz, E. and Vock, P. (1990). Spiral volumetric CT with single-breath-hold technique, continuous transport, and continuous scanner rotation, Radiology, 176, 181-183 crossref(new window)

9.
Lester, H. and Arridge S. R. (1999). A survey of Hierarchical non-linear medical image registration, Pat-tern Recognition, 32, 129-149 crossref(new window)

10.
West, J., Fitzpatrick, J. M., Wang, M. Y., Dawant, B. M., Maurer, C. R., Kessler, R. M. and Maciunas, R. J. (1999). Retrospective intermodality registralion techniques for images of the head: Surface-based versus volume-based, IEEE Transactions on Medical Imaging, 18, 144-150 crossref(new window)

11.
Zaho, W. and Rowlands, J. A. (1995). X-ray imaging using amorphous selenium: Feasibility of a flat panel self-scanned detector for digital radiology, Medical Physics, 22, 1595-1604 crossref(new window)

12.
Zitova, B. and Flusser, J. (2003). Image registration methods: A survey, Image and Vision Computing, 21, 977-1000 crossref(new window)