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Undersampled dynamic X-ray tomography with dimension reduction Kalman filter
Undersampled dynamic X-ray tomography with dimension reduction Kalman filter
- Publication Year :
- 2018
-
Abstract
- In this paper, we consider prior-based dimension reduction Kalman filter for undersampled dynamic X-ray tomography. With this method, the X-ray reconstructions are parameterized by a low-dimensional basis. Thus, the proposed method is a) computationally very light; and b) extremely robust as all the computations can be done explicitly. With real and simulated measurement data, we show that the method provides accurate reconstructions even with very limited number of angular directions.
- Subjects :
- Statistics - Computation
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1805.00871
- Document Type :
- Working Paper