Abstract
We introduce a graph Laplacian-based algorithm for the tomographic reconstruction of a planar object from its projections taken at random unknown directions. A Laplace-type operator is constructed on the data set of projections, and the eigenvectors of this operator reveal the projection orientations. The algorithm is shown to successfully reconstruct the Shepp-Logan phantom from its noisy projections. Such a reconstruction algorithm is desirable for the structuring of certain biological proteins using cryo-electron microscopy.
Original language | English (US) |
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Pages (from-to) | 1891-1899 |
Number of pages | 9 |
Journal | IEEE Transactions on Image Processing |
Volume | 17 |
Issue number | 10 |
DOIs | |
State | Published - 2008 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Software
- Computer Graphics and Computer-Aided Design
Keywords
- Dimensionality reduction
- Graph laplacian
- Tomography