Geostatistical Medial Image Registration

J. Ruiz-Alzola, E. Suarez, C. Alberola-Lopez, S. K. Warfield, C.-F. Westin
Sixth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'03)
Pages 894-901
November, 2003

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Abstract

We propose a novel approach to landmark-based medical image registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated using generalpurpose registration algorithms, in order to construct an optimum predictor of the displacement field. High accuracy is achieved by using an estimated spatial model of the displacement field directly from the image data, while practically circumventing the difficulties that prevented Kriging from being widely used in image registration.

Registration results (see text). (a) axial T1 (b) axial T2 (c) warped axial T2. (d) first sagittal T1 (e) second sagittal T1 (f) warped second sagittal

Reference

Ruiz-Alzola J, Suarez E, Alberola-Lopez C, Warfield SK, Westin CF. Geostatistical medial image registration. In Sixth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'03). Montreal, Canada, 2003;894-901.

Bibtex entry

@InProceedings{ruiz-alzolaMICCAI03,
  author         = {J. Ruiz-Alzola and E. Suarez and C. Alberola-Lopez  and S. 
                   K. Warfield and C.-F. Westin},                              
  title          = {Geostatistical Medial Image Registration},                 
  booktitle      = {Sixth International Conference on Medical Image Computing  
                   and  Computer-Assisted Intervention (MICCAI'03)},           
  pages          = {894--901},                                                 
  year           = 2003,                                                       
  address        = {Montreal, Canada},                                         
  month          = {November}
}

Grants

NIH P41-RR13218 (NAC), TIC2001-3808-C02, CIMIT

Research areas

DTMRI, Tensor

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