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Article
Report number	arXiv:1802.05366
Title	MARS-MD: rejection based image domain material decomposition
Related title	MARS-MD: rejection based image domain material decomposition
Author(s)	Bateman, C.J. (MARS Bioimaging ; U. Otago, Dept. Radiol. ; Canterbury U. ; Lincoln Agritech Limited, New Zealand) ; Knight, D. (U. Otago, Dept. Radiol.) ; Brandwacht, B. (Twente U., Enschede) ; Mahon, J., MC (Canterbury U.) ; Healy, J. (U. Canterbury, Dept. Biol.) ; Panta, R. (U. Otago, Dept. Radiol. ; MARS Bioimaging) ; Aamir, R. (U. Otago, Dept. Radiol.) ; Rajendran, K. (U. Otago, Dept. Radiol.) ; Moghiseh, M. (U. Otago, Dept. Radiol.) ; Ramyar, M. (U. Otago, Dept. Radiol.) ; Rundle, D. (MARS Bioimaging) ; Bennett, J. (MARS Bioimaging) ; de Ruiter, N. (U. Otago, Dept. Radiol. ; MARS Bioimaging ; HIT Lab NZ) ; Smithies, D. (MARS Bioimaging) ; Bell, S.T. (MARS Bioimaging) ; Doesburg, R. (MARS Bioimaging) ; Chernoglazov, A. (MARS Bioimaging ; HIT Lab NZ) ; Mandalika, V.B.H. (MARS Bioimaging ; HIT Lab NZ) ; Walsh, M. (MARS Bioimaging) ; Shamshad, M. (U. Otago, Dept. Radiol. ; MARS Bioimaging) ; Anjomrouz, M. (U. Otago, Dept. Radiol. ; MARS Bioimaging) ; Atharifard, A. (U. Otago, Dept. Radiol.) ; Broeke, L. Vanden (Canterbury U.) ; Bheesette, S. (U. Otago, Dept. Radiol. ; CERN) ; Kirkbride, T. (Ara institute of canterbury) ; Anderson, N.G. (U. Otago, Dept. Radiol.) ; Gieseg, S.P. (U. Otago, Dept. Radiol. ; U. Canterbury, Dept. Biol.) ; Woodfield, T. (U. Otago, Dept. Radiol.) ; Renaud, P.F. (U. Otago, Dept. Radiol. ; Canterbury U.) ; Butler, A.P.H. (CERN ; U. Otago, Dept. Radiol. ; MARS Bioimaging) ; Butler, P.H. (CERN ; MARS Bioimaging ; Canterbury U.)
Publication	2018-03-16
Imprint	2018-02-14
In:	JINST 13 (2018) P05020-P05020
DOI	10.1088/1748-0221/13/05/P05020
Subject category	Detectors and Experimental Techniques
Abstract	This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.
Copyright/License	arXiv nonexclusive-distrib. 1.0 publication: © 2018 CERN (License: CC-BY-3.0)

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