Incorporating DTI data as a constraint in deformation tensor morphometry between T1 MR images

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4584 LNCS, Issue , 2007, Pages 223-232

  Studholme, Colin ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; BRAIN; DISEASES; PROBABILITY DISTRIBUTIONS; TENSORS;

MUTUAL INFORMATION (MI); TISSUE LOSS PATTERNS; VISCOUS FLUID REGISTRATION;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ALZHEIMER DISEASE; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; EVALUATION; FACTUAL DATABASE; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; METHODOLOGY; MYELINATED NERVE; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; BRAIN; DATABASES, FACTUAL; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 34548379097     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_19     Document Type: Conference Paper

References (20)

1. Alexander, D.C., Gee, J.C., Bajcsy, R.K.: Strategies for data reorientation during nonrigid warps of diffusion tensor image. In: Taylor, C., Colchester, A. (eds.) MICCAI'99. LNCS, vol. 1679, pp. 463-472. Springer, Heidelberg (1999)
2. Basser, P.J., Mattiello, J., Bihan, D.L.: Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Mag. Res. 103, 247-254 (1994)
3. Cao, Y., Miller, M., Mori, S., Winslow, R., Younes, L.: Large deformation diffeomorphic metric mapping of fiber orientations. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, IEEE 2005 (2005)
4. Cao, Y., Miller, M., Mori, S., Winslow, R., Younes, L.: Diffeomoprphic matching of diffusion tensor images. In: Proceedings of the Computer Vision and Pattern Recognition Workshop (2006)
5. Cardenas, V.A., Studholme, C., Gazdzinski, S., Durazzo, T.C., Meyerhoff, D.J.: Deformation based morphometry of brain changes in alcohol dependence and abstinence. Neuroimage 34, 879-887 (2007)
6. Christensen, G.E., Miller, M.I., Vannier, M.W.: Individualizing neuroanatomical atlases using a massively parallel computer. Computer, pp. 32-38 (1996)
7. D'Agostino, E., Maes, F., Vandermeulen, D., Suetens, P.: A viscous fluid model for multimodal non-rigid image registration using mutual information. Medical Image Analysis 7, 565-575 (2003)
8. Freeborough, P.A., Fox, N.C.: Modeling brain deformations in Alzheimer's disease by fluid registration of serial 3D MR images. Journal of Computer Assisted Tomography 22(5), 838-843 (1998)
9. Hermosillo, G., Chefd'hotel, C., Faugeras, O.: Variational methods for multimodal image matching. International Journal of Computer Vision 50(3), 329-343 (2002)
10. Jernigan, T.L., Archibald, S.L., Fennema-Notestine, C., Gamst, A.C., Stout, J.C., Bonner, J., Hesselink, J.R.: Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiology of Aging 22(4), 581-591 (2001)
11. Pluim, J., Maintz, J.B., Viegever, M.A.: Mutual-information-based registration of medical images: A survey. IEEE Transactions on Medical Imaging 22(8), 986-1004 (2003)
12. Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C Cambridge University Press, Cambridge, England (1992)
13. Studholme, C., Constable, R.T., Duncan, J.S.: Accurate alignment of functional EPI data to anatomical MRI using a physics based distortion model. IEEE Transactions on Medical Imaging 19(11), 1115-1127 (2000)
14. Studholme, C., Drapaca, C., Iordanova, B., Cardenas, V.: Deformation based mapping of volume change from serial brain MRI in the presence of local tissue contrast change. IEEE transactions on Medical Imaging 25(5), 626-639 (2006)
15. Studholme, C., Hill, D.L.G., Hawkes, D.: Incorporating connected region labelling into automated image registration using mutual information. In: Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pp. 23-31. IEEE Computer Society Press, Washington, DC, USA (1996)
16. Studholme, C., Hill, D.L.G., Hawkes, D.J.: An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognition 32(1), 71-86 (1999)
17. Studholme, C., Hill, D.L.G., Maisey, M.N., Hawkes, D.: Registration measures for automated 3D alignment of PET and intensity distorted MR images. In: Proceedings in Image Fusion and Shape Variability Techniques, pp. 186-193. Leeds University Press (1996)
18. Thevenaz, P., Unser, M.: Optimization of mutual information for multiresolution image registration. IEEE Transactions on Image Processing 9(12), 2083-2099 (2000)
19. Wahba, G.: Spline Models for Observational Data. Society for Industrial and Applied Mathematics, Philadelphia (1990)
20. Zhang, H., Yushkevich, P.A., Alexander, D.C., Gee, J.C.: Deformable registration of diffusion tensor MR images with explicit orientation optimization. Medical Image Analysis 10(5), 764-785 (2000)