Geometric kernel smoothing of tensor fields

Statistics – Methodology

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

14 figures

Scientific paper

In this paper, we study a kernel smoothing approach for denoising a tensor field. Particularly, both simulation studies and theoretical analysis are conducted to understand the effects of the noise structure and the structure of the tensor field on the performance of different smoothers arising from using different metrics, viz., Euclidean, log-Euclidean and affine invariant metrics. We also study the Rician noise model and compare two regression estimators of diffusion tensors based on raw diffusion weighted imaging data at each voxel.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Geometric kernel smoothing of tensor fields does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Geometric kernel smoothing of tensor fields, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Geometric kernel smoothing of tensor fields will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-221410

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.