Tomosynthesis via total variation minimization reconstruction and Prior Image Constrained Compressed Sensing (PICCS) on a C-arm system

Brian Nett, Jie Tang, Shuai Leng, Guang Hong Chen

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

35 Scopus citations

Abstract

Recently, foundational mathematical theory, compressed sensing (CS), has been developed which enables accurate reconstruction from greatly undersampled frequency information (Candes et. al. and Donoho). Using numerical phantoms it has been demonstrated that CS reconstruction (e.g. minimizing the ℓ1 norm of the discrete gradient of the image) offers promise for computed tomography. However, when using experimental CT projection data the undersampling factors enabled were smaller than in numerical simulations. An extension to CS has recently been proposed wherein a prior image is utilized as a constraint in the image reconstruction procedure (i.e. Prior Image Constrained Compressed Sensing - PICCS). Experimental results are demonstrated here from a clinical C-arm system, highlighting one application of PICCS in reducing radiation exposure during interventional procedures while preserving high image quality. In this study a range of view angles has been investigated from very limited angle aquisitions (e.g. tomosythesis) to undersampled CT acquisitions.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2008 - Physics of Medical Imaging
DOIs
StatePublished - 2008
EventMedical Imaging 2008 - Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 18 2008Feb 21 2008

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6913
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2008 - Physics of Medical Imaging
Country/TerritoryUnited States
CitySan Diego, CA
Period2/18/082/21/08

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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