Joint reconstruction in low dose multi-energy CT
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CitationToivanen, Jussi. Meaney, Alexander. Siltanen, Samuli. Kolehmainen, Ville. (2020). Joint reconstruction in low dose multi-energy CT. Inverse problems and imaging, 14 (4) , 607-629. 10.3934/ipi.2020028.
Multi-energy CT takes advantage of the non-linearly varying at-tenuation properties of elemental media with respect to energy, enabling moreprecise material identification than single-energy CT. The increased precisioncomes with the cost of a higher radiation dose. A straightforward way to lowerthe dose is to reduce the number of projections per energy, but this makestomographic reconstruction more ill-posed. In this paper, we propose how thisproblem can be overcome with a combination of a regularization method thatpromotes structural similarity between images at different energies and a suit-ably selected low-dose data acquisition protocol using non-overlapping projec-tions. The performance of various joint regularization models is assessed withboth simulated and experimental data, using the novel low-dose data acquisi-tion protocol. Three of the models are well-established, namely the joint totalvariation, the linear parallel level sets and the spectral smoothness promotingregularization models. Furthermore, one new joint regularization model is in-troduced for multi-energy CT: a regularization based on the structure functionfrom the structural similarity index. The findings show that joint regulariza-tion outperforms individual channel-by-channel reconstruction. Furthermore,the proposed combination of joint reconstruction and non-overlapping projec-tion geometry enables significant reduction of radiation dose