Diffusion tensor image up-sampling: A registration-based approach

Magnetic Resonance Imaging

Volumn 28, Issue 10, 2010, Pages 1497-1506

  Mai, Zhenhua ^a   Verhoye, Marleen ^a   Van der Linden, Annemie ^a   Sijbers, Jan ^a  

^a UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

DWI DTI; Registration based; Up sampling

Indexed keywords

ACCURACY; ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; DIFFUSION TENSOR IMAGING; IMAGE ANALYSIS; IMAGE PROCESSING; PHANTOM; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

ALGORITHMS; BRAIN; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 78449249671     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mri.2010.06.018     Document Type: Article

References (24)

1. Udupa J.K., Herman G.T. 3D imaging in medicine 1991, CRC Press, Inc.,, Boca Baton, Florida.
2. Grevera G.J., Udupa J.K. An objective comparison of 3-d image interpolation methods. IEEE Trans Med Imaging 1998, 17(4):642-652.
3. Meijering E.H.W., Niessen W.J., Viergever M.A. Quantitative evaluation of convolution-based methods for medical image interpolation. Med Image Anal 2001, 5(2):111-126.
4. Thévenaz P., Blu T., Unser M. Interpolation revisited. IEEE Trans Med Imaging 2000, 19(7):739-758.
5. Goshtasby A., Turner D.A., Ackerman V. Matching of tomographic slices for interpolation. IEEE Trans Med Imaging 1992, 11(4):507-516.
6. ITK. Insight Toolkit. , 2009. http://www.itk.org.
7. Tschumperle D., Deriche R. Diffusion PDE's on vector-valued images: local approach and geometric viewpoint. IEEE Signal Process Mag 2002, 19(5):16-25.
8. Alexander D.C., Gee J.C., Bajcsy R. Strategies for data reorientation during non-rigid warps of diffusion tensor images. Lect Notes Comput Sci 1999, 1679:463-472.
9. Rohde G.K., Pajevic S., Pierpaoli C. Multi-channel registration of diffusion tensor images using directional information. In IEEE International Symposium on Biomedical Imaging 2004, 712-715.
10. Van Hecke W., Leemans A., d' Agostino E., De Backer S., Vandervliet E., Parizel P., et al. Nonrigid coregistration of diffusion tensor images using a viscous fluid model and mutual information. IEEE Trans Med Imaging 2007, 26(11):1598-1612.
11. Studholme C. Dense feature deformation morphometry: incorporating DTI data into conventional MRI morphometry. Med Image Anal 2008, 12(6):742-751.
12. Chao T.C., Chou M.C., Yang P., Chung H.W., Wu M.T. Effects of interpolation methods in spatial normalization of diffusion tensor imaging data on group comparison of fractional anisotropy. Magn Reson Imaging Jun 2009, 27(5):681-690.
13. Pennec X., Fillard P., Ayache N. A Riemannian framework for tensor computing. In Int J Comput Vision 2006, 66(1):41-66.
14. Beauchemin S.S., Barron J.L. The computation of optical flow 1995, ACM New York.
15. Tekalp A.M. Digital Video Processing 1995, Prentice-Hall.
16. Lee S., Wolberg G., Chwa K.Y., Shin S.Y. Image metamorphosis with scattered feature constraints. In IEEE Transactions on Visualization and Computer Graphics 1996, Vol. 2:337-345. No. 4.
17. Lee S., Wolberg G., Shin S.Y. Scattered data interpolation with multilevel B-splines. In IEEE Transactions on Visualization and Computer Graphics 1997, Vol. 3:228-244. No. 3.
18. Lucas B., Kanade T. An iterative image registration technique with an application in stereo vision. In Seventh International Joint Conference on Artificial Intelligence (IJCAI-81) 1981, 674-679.
19. Park H.J., Kubicki M., Shenton M.E., Guimond A., McCarley R.W., Maier S.E., et al. Spatial normalization of diffusion tensor MRI using multiple channels. Neuroimage 2003, 20(4):1995-2009.
20. Penney G.P., Schnabel J.A., Rueckert D., Viergever M.A. Registration-based interpolation. IEEE Trans Med Imaging 2004, 23(7):922-926.
21. Frakes D.H., Dasi L.P., Pekkan K., Kitajima H.D., Sundareswaran K., Yoganathan A.P., et al. A new method for registration-based medical image interpolation. IEEE Trans Med Imaging 2008, 27(3):370-377.
22. Cao Y., Miller M.I., Winslow R.L., Younes L. Large deformation diffeomorphic metric mapping of vector fields. IEEE Trans Med Imaging 2005, 24(9):1216-1230.
23. Meijering E.H.W., Niessen W.J., Josien P., Viergever M.A. Quantitative Comparison of sinc-approximating kernels for medical image interpolation. In MICCAI 1997, 210-217.
24. NA-MIC The National Alliance for Medical Imaging Computing 2006, http://www.na-mic.org.