Non-convex prior image constrained compressed sensing (NC-PICCS)

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2010
Subtitle of host publicationPhysics of Medical Imaging
EditionPART 2
DOIs
StatePublished - Dec 1 2010
EventMedical Imaging 2010: Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 15 2010Feb 18 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 2
Volume7622
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2010: Physics of Medical Imaging
CountryUnited States
CitySan Diego, CA
Period2/15/102/18/10

Keywords

  • Compressed sensing
  • Computed tomography
  • Low dose CT
  • Noise reduction
  • PICCS
  • Radiation dose reduction

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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