TV-constrained incremental algorithms for low-intensity CT image reconstruction

Sean D. Rose, Martin S. Andersen, Emil Y. Sidky, Xiaochuan Pan

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Low-dose X-ray computed tomography (CT) has garnered much recent interest as it provides a method to lower patient dose and simultaneously reduce scan time. In non-medical applications the possibility of preventing sample damage makes low-dose CT desirable. Reconstruction in low-dose CT poses a significant challenge due to the high level of noise in the data. Here we propose an iterative method for reconstruction which minimizes the transmission Poisson likelihood subject to a total-variation constraint. This formulation accommodates efficient methods of parameter selection because the choice of TV constraint can be guided by an image reconstructed by filtered backprojection (FBP). We apply our algorithm to low-dose synchrotron X-ray CT data from the Advanced Photon Source (APS) at Argonne National Labs (ANL) to demonstrate its potential utility. We find that the algorithm provides a means of edge-preserving regularization with the potential to generate useful images at low iteration number in low-dose CT.
Original languageEnglish
Title of host publication Proceedings of the 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Number of pages3
Publication date2015
ISBN (Print)978-1-4673-9862-6
Publication statusPublished - 2015
Event2015 Nuclear Science Symposium and Medical Imaging Conference - Town and Country Hotel, San Diego, United States
Duration: 31 Oct 20157 Nov 2015


Conference2015 Nuclear Science Symposium and Medical Imaging Conference
LocationTown and Country Hotel
Country/TerritoryUnited States
CitySan Diego


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