CAN ANISOTROPIC IMAGES BE UPSAMPLED?

Mads F. Hansen, Thomas H. Mosbech, Hildur Ólafsdóttir, Michael S. Hansen, Rasmus Larsen

2010

Abstract

This paper presents a novel method for upsampling anisotropic medical gray-scale images. The resolution is increased by fitting an image function, modeled by cubic B-splines, to the slices. The method simulates the observed slices with an image function and iteratively updates the function by comparing the simulated slices with observed slices. The approach handles partial voluming by modeling the thickness of the slices. The formulation is ill-posed, and thus a prior needs to be included. Correspondences between adjacent slices are established using a symmetric registration method with a free-form deformation model. The correspondences are then converted into a prior that penalizes gradients along lines of correspondence. Tests on the Shepp-Logan phantom show promising results, and the approach performs better than methods such as cubic interpolation and one-way registration-based interpolation.

References

  1. Canny, J. (1986). A computational approach to edge detection. IEEE Transactions Pattern Analysis and Machine Intelligence, 8(6):679-698.
  2. Frakes, D., Dasi, L., Pekkan, K., Kitajima, H., Sundareswaran, K., Yoganathan, A., and Smith, M. (2008). A New Method for Registration-based Medical Image Interpolation. IEEE Transactions on Medical Imaging, 27(3):370-377.
  3. Gudbjartsson, H. and Patz, S. (1995). The rician distribution of noisy mri data. Magnetic Resonance in Medicine, 34(6):910-914.
  4. Keys, R. G. (1981). Cubic Convolution Interpolation for Digital Image Processing. IEEE Transactions on Acoustics Speech and Signal Processing, 29(6):1153- 1160.
  5. O lafsdóttir, H., Pedersen, H., Hansen, M. S., Lyksborg, M., Darkner, S., and Larsen, R. (2010). Registration-based Interpolation Applied to Cardiac MR. Proceedings of SPIE Medical Imaging 2010: Image Processing.
  6. Pennec, X., Stefanescu, R., Arsigny, V., Fillard, P., and Ayache, N. (2005). Riemannian Elasticity: A Statistical Regularization Framework for Non-linear Registration. Proceedings of the 8th International Conference on Medical Image Computing and ComputerAssisted Interventation (LNCS), 3750:943-950.
  7. Penney, G., Schnabel, J., Rueckert, D., Viergever, M., and Niessen, W. (2004). Registration-based Interpolation. IEEE Transactions on Medical Imaging, 21(7):922- 926.
  8. Rueckert, D., Sonoda, L. I., Hayes, C., Hill, D. L. G., Leach, M. O., and Hawkes, D. J. (1999). Nonrigid Registration using Free-Form Deformations: Application to Breast MR Images. IEEE Transactions on Medical Imaging, 18(8):712-21.
  9. Shepp, L. A. and Logan, B. F. (1974). The Fourier reconstruction of a head section. IEEE Transactions on Nuclear Science, 21(3):21-43.
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Paper Citation


in Harvard Style

F. Hansen M., H. Mosbech T., Ólafsdóttir H., S. Hansen M. and Larsen R. (2010). CAN ANISOTROPIC IMAGES BE UPSAMPLED? . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 76-81. DOI: 10.5220/0002846500760081


in Bibtex Style

@conference{visapp10,
author={Mads F. Hansen and Thomas H. Mosbech and Hildur Ólafsdóttir and Michael S. Hansen and Rasmus Larsen},
title={CAN ANISOTROPIC IMAGES BE UPSAMPLED?},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={76-81},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002846500760081},
isbn={978-989-674-028-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - CAN ANISOTROPIC IMAGES BE UPSAMPLED?
SN - 978-989-674-028-3
AU - F. Hansen M.
AU - H. Mosbech T.
AU - Ólafsdóttir H.
AU - S. Hansen M.
AU - Larsen R.
PY - 2010
SP - 76
EP - 81
DO - 10.5220/0002846500760081