SLLE: Spherical locally linear embedding with applications to tomography

Yi Fang, Mengtian Sun, S. V.N. Vishwanathan, Karthik Ramani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The tomographic reconstruction of a planar object from its projections taken at random unknown view angles is a problem that occurs often in medical imaging. Therefore, there is a need to robustly estimate the view angles given random observations of the projections. The widely used locally linear embedding (LLE) technique provides nonlinear embedding of points on a flat manifold. In our case, the projections belong to a sphere. Therefore, we extend LLE and develop a spherical locally linear embedding (sLLE) algorithm, which is capable of embedding data points on a non-flat spherically constrained manifold. Our algorithm, sLLE, transforms the problem of the angle estimation to a spherically constrained embedding problem. It considers each projection as a high dimensional vector with dimensionality equal to the number of sampling points on the projection. The projections are then embedded onto a sphere, which parametrizes the projections with respect to view angles in a globally consistent manner. The image is reconstructed from parametrized projections through the inverse Radon transform. A number of experiments demonstrate that sLLE is particularly effective for the tomography application we consider. We evaluate its performance in terms of the computational efficiency and noise tolerance, and show that sLLE can be used to shed light on the other constrained applications of LLE.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Pages1129-1136
Number of pages8
DOIs
StatePublished - Sep 22 2011
Event2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, CO, United States
Duration: Jun 20 2011Jun 25 2011

Other

Other2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
CountryUnited States
CityColorado Springs, CO
Period6/20/116/25/11

Fingerprint

Tomography
Radon
Medical imaging
Computational efficiency
Sampling
Experiments

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Fang, Y., Sun, M., Vishwanathan, S. V. N., & Ramani, K. (2011). SLLE: Spherical locally linear embedding with applications to tomography. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 (pp. 1129-1136). [5995563] https://doi.org/10.1109/CVPR.2011.5995563

SLLE : Spherical locally linear embedding with applications to tomography. / Fang, Yi; Sun, Mengtian; Vishwanathan, S. V.N.; Ramani, Karthik.

2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. p. 1129-1136 5995563.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fang, Y, Sun, M, Vishwanathan, SVN & Ramani, K 2011, SLLE: Spherical locally linear embedding with applications to tomography. in 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011., 5995563, pp. 1129-1136, 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011, Colorado Springs, CO, United States, 6/20/11. https://doi.org/10.1109/CVPR.2011.5995563
Fang Y, Sun M, Vishwanathan SVN, Ramani K. SLLE: Spherical locally linear embedding with applications to tomography. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. p. 1129-1136. 5995563 https://doi.org/10.1109/CVPR.2011.5995563
Fang, Yi ; Sun, Mengtian ; Vishwanathan, S. V.N. ; Ramani, Karthik. / SLLE : Spherical locally linear embedding with applications to tomography. 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. pp. 1129-1136
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