Translator Disclaimer
22 March 2010 Non-convex prior image constrained compressed sensing (NC-PICCS)
Author Affiliations +
The purpose of this paper is to present a new image reconstruction algorithm for dynamic data, termed non-convex prior image constrained compressed sensing (NC-PICCS). It generalizes the prior image constrained compressed sensing (PICCS) algorithm with the use of non-convex priors. Here, we concentrate on perfusion studies using computed tomography examples in simulated phantoms (with and without added noise) and in vivo data, to show how the NC-PICCS method holds potential for dramatic reductions in radiation dose for time-resolved CT imaging. We show that NC-PICCS can provide additional undersampling compared to conventional convex compressed sensing and PICCS, as well as, faster convergence under a quasi-Newton numerical solver.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan Carlos Ramírez Giraldo, Joshua D. Trzasko, Shuai Leng, Cynthia H. McCollough, and Armando Manduca "Non-convex prior image constrained compressed sensing (NC-PICCS)", Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76222C (22 March 2010);

Back to Top