Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data

Sean Rose, Martin Skovgaard Andersen, Emil Y. Sidky, Xiaochuan Pan

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Abstract

This conference contribution adapts an incremental framework for solving optimization problems of interest for sparse-view CT. From the incremental framework two algorithms are derived: one that combines a damped form of the algebraic reconstruction technique (ART) with a total-variation (TV) projection, and one that employs a modified damped ART, accounting for a weighted-quadratic data fidelity term, combined with TV projection. The algorithms are demonstrated on simulated, noisy, sparseview CT data.
Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography
Publication date2014
Pages351-354
Publication statusPublished - 2014
Event3rd International Conference on Image Formation in X-Ray Computed Tomography - Fort Douglas/Olympic Village, Salt Lake City, Utah, United States
Duration: 22 Jun 201425 Jun 2014
Conference number: 3
http://www.ucair.med.utah.edu/CTmeeting/

Conference

Conference3rd International Conference on Image Formation in X-Ray Computed Tomography
Number3
LocationFort Douglas/Olympic Village
CountryUnited States
CitySalt Lake City, Utah
Period22/06/201425/06/2014
Internet address

Cite this

Rose, S., Andersen, M. S., Sidky, E. Y., & Pan, X. (2014). Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data. In Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography (pp. 351-354)