When do the iterative reconstruction methods become worth the effort?

A driving force for the development of new reconstruction algorithms is to achieve better quality images using less information (lower dose, fewer projections, in less time), but under what circumstances do iterative methods become worth the effort? In this paper we propose a framework that enables the performance of reconstruction algorithms to be mapped. Such a framework allows fair comparisons to be made, providing insights into experimental acquisition strategies and methods of quantifying the quality of reconstructions, and identifying the sweet spot for different algorithms. 




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