Literature DB >> 8287354

Using kriging for 3D medical imaging.

M R Stytz1, R W Parrott.   

Abstract

We describe our implementation of kriging for interpolation of scalar values in three-dimensional medical image surface rendering and for slice interpolation. Kriging is an interpolation technique developed in the geosciences for estimating ore deposit spatial distributions. Kriging has been mathematically proven to be the best (statistically optimal) linear unbiased estimation technique for spatially distributed data. As a byproduct of the kriging technique, kriging can calculate the estimation error for the interslice interpolated values. Kriging also offers the potential for quantifying the interpolation error in slices computed by the estimation technique. This paper presents the initial results obtained using kriging for the pre-processing operations of slice interpolation by slice-value interpolation and interpolating voxel values during iso-surface extraction. We found that kriging is an accurate interpolation technique for surface rendering and for slice interpolation. Our results indicate that kriging can duplicate the rendering results obtained with other interpolation techniques and it offers the potential for providing visually "better" images than are obtained using the other interpolation techniques we tested.

Mesh:

Year:  1993        PMID: 8287354     DOI: 10.1016/0895-6111(93)90059-v

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  5 in total

1.  Research on interpolation methods in medical image processing.

Authors:  Mei-Sen Pan; Xiao-Li Yang; Jing-Tian Tang
Journal:  J Med Syst       Date:  2010-07-06       Impact factor: 4.460

2.  Gaussian process interpolation for uncertainty estimation in image registration.

Authors:  Christian Wachinger; Polina Golland; Martin Reuter; William Wells
Journal:  Med Image Comput Comput Assist Interv       Date:  2014

3.  Contour-Driven Atlas-Based Segmentation.

Authors:  Christian Wachinger; Karl Fritscher; Greg Sharp; Polina Golland
Journal:  IEEE Trans Med Imaging       Date:  2015-06-09       Impact factor: 10.048

4.  Uncertainty-aware asynchronous scattered motion interpolation using Gaussian process regression.

Authors:  Bojan Kocev; Horst Karl Hahn; Lars Linsen; William M Wells; Ron Kikinis
Journal:  Comput Med Imaging Graph       Date:  2018-12-21       Impact factor: 4.790

5.  Gaussian process regression for ultrasound scanline interpolation.

Authors:  Alperen Degirmenci; Robert D Howe; Douglas P Perrin
Journal:  J Med Imaging (Bellingham)       Date:  2022-05-17
  5 in total

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