TY - CONF
T1 - Skull-based registration of intra-subject CT images: The effects of different resolutions and partial contents
T2 - 2010 International Conference on Bioinformatics and Biomedical Technology, ICBBT 2010
AU - Liao, Yuan-Lin
AU - Sun, Yung-Nien
AU - Lu, Chia-Feng
AU - Wu, Yu-Te
AU - Wu, Chieh-Tsai
AU - Lee, Shih-Tseng
AU - Lee, Jiann-Der
AU - (IACSIT), Int. Assoc. Comput. Sci. Inf. Technol.
N1 - 會議代碼: 81050
被引用次數：2
Export Date: 31 March 2016
通訊地址: Liao, Y.-L.; Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan; 電子郵件： [email protected]
參考文獻: Gholipour, A., Kehtarnavaz, N., Briggs, R., Devous, M., Gopinath, K., Brain functional localization: A survey of image registration techniques (2007) IEEE Trans. Med. Imaging, 26, pp. 427-451. , April; Hutton, B.F., Braun, M., Thurfjell, L., Lau, D.Y.H., Image registration: An essential tool for nuclear medicine (2002) Eur. J. Nucl. Med., 29, pp. 559-577. , April; Turkington, T.G., Hoffman, J.M., Jaszczak, R.J., MacFall, J.R., Harris, C.C., Kilts, C.D., Accuracy of surface fit registration for PET and MR brain images using full and incomplete brain surfaces (1995) J. Comput. Assist. Tomogr., 19, pp. 117-124. , January/February; Van Herk, M., Gilhuijs, K.G.A., De Munck, J., Touw, A., Effect of image artifacts, organ motion, and poor segmentation on the reliability and accuracy of three-dimensional chamfer matching (1997) Computer Aided Surgery, 2 (6), pp. 346-355. , DOI 10.1002/(SICI)1097-0150(1997)2:6<346::AID-IGS5>3.0.CO;2-#; Rusinek, H., Tsui, W.H., Levy, A.V., Noz, M.E., De Leon, M.J., Principal axes and surface fitting methods for three-dimensional image registration (1993) J. Nucl. Med., 34, pp. 2019-2024. , November; Li, X., Zhang, P., Brisman, R., Kutcher, G., Use of simulated annealing for optimization of alignment parameters in limited MRI acquisition volumes of the brain (2005) Med. Phys., 32, pp. 2363-2370. , July; Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P., Multimodality image registration by maximization of mutual information (1997) IEEE Trans. Med. Imaging, 16, pp. 187-198. , April; Roche, A., Malandain, G., Pennec, X., Ayache, N., The correlation ratio as a new similarity measure for multimodal image registration (1998) Lect. Notes Comput. Sci., 1496, pp. 1115-1124. , (Proc. MICCAI'98); Besl, P.J., McKay, N.D., A method for registration of 3-D shapes (1992) IEEE Trans. Pattern Anal. Mach. Intell., 14, pp. 239-256. , February; Brogefors, G., Hierarchical chamfer matching: A parametric edge matching algorithm (1988) IEEE Trans. Pattern Anal. Mach. Intell., 10, pp. 849-865. , November; Pelizzari, C.A., Chen, G.T.Y., Spelbring, D.R., Weichselbaum, R.R., Chen, C.-T., Accurate three-dimensional registration of CT, PET, and/or MR images of the brain (1989) J. Comput. Assist. Tomogr., 13, pp. 20-26. , January/February; Press, W.H., (1992) Numerical Recipes in C: The Art of Scientific Computing, , Cambridge: Cambridge University Press;
PY - 2010
Y1 - 2010
N2 - The performance of a skull-based image registration is assessed for aligning intra-subject computed tomography (CT) images. Images with six levels of resolution are provided. The images with coarser resolution are resampled, followed by thresholding all images to extract the skull as the matching feature. Using the finest image as the reference, the skull-based registration is processed with sum of squared difference (SSD) criterion. In addition, images with partial contents are simulated and served as the floating image to investigate the interaction between different levels of resolution and partial contents. We conclude that a successful registration requires that more than half of the content should be preserved and the differences of image resolution between two images should be less than 16 times. © 2010 IEEE.
AB - The performance of a skull-based image registration is assessed for aligning intra-subject computed tomography (CT) images. Images with six levels of resolution are provided. The images with coarser resolution are resampled, followed by thresholding all images to extract the skull as the matching feature. Using the finest image as the reference, the skull-based registration is processed with sum of squared difference (SSD) criterion. In addition, images with partial contents are simulated and served as the floating image to investigate the interaction between different levels of resolution and partial contents. We conclude that a successful registration requires that more than half of the content should be preserved and the differences of image resolution between two images should be less than 16 times. © 2010 IEEE.
KW - Computed tomography
KW - Image registration
KW - Partial
KW - Resolution
KW - Skull
KW - Coarser resolution
KW - CT Image
KW - Sum of squared differences
KW - Thresholding
KW - Bioinformatics
KW - Feature extraction
KW - Image resolution
KW - Computerized tomography
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-77954505639&partnerID=40&md5=34ce4f429299636a39b4c52b19b7a129
UR - https://www.scopus.com/results/citedbyresults.uri?sort=plf-f&cite=2-s2.0-77954505639&src=s&imp=t&sid=f208a50274cb7705d6fd7d4249fa0be5&sot=cite&sdt=a&sl=0&origin=recordpage&editSaveSearch=&txGid=a30788060a0067c0a357ac5eff88917e
U2 - 10.1109/ICBBT.2010.5478962
DO - 10.1109/ICBBT.2010.5478962
M3 - Other
SP - 269
EP - 272
ER -