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Undersampled dynamic X-ray tomography with dimension reduction Kalman filter

Undersampled dynamic X-ray tomography with dimension reduction Kalman filter

Authors :
Hakkarainen, Janne
Purisha, Zenith
Solonen, Antti
Siltanen, Samuli
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

Subjects :
Statistics - Computation

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1805.00871
Document Type :
Working Paper