Optimization-based reconstruction of sparse images from few-view projections.

Xiao Han, Junguo Bian, Erik L. Ritman, Emil Y. Sidky, Xiaochuan Pan

Research output: Contribution to journalArticlepeer-review

85 Scopus citations


In this work, we investigate optimization-based image reconstruction from few-view (i.e. less than ten views) projections of sparse objects such as coronary-artery specimens. Using optimization programs as a guide, we formulate constraint programs as reconstruction programs and develop algorithms to reconstruct images through solving the reconstruction programs. Characterization studies are carried out for elucidating the algorithm properties of 'convergence' (relative to designed solutions) and 'utility' (relative to desired solutions) by using simulated few-view data calculated from a discrete FORBILD coronary-artery phantom, and real few-view data acquired from a human coronary-artery specimen. Study results suggest that carefully designed reconstruction programs and algorithms can yield accurate reconstructions of sparse images from few-view projections.

Original languageEnglish (US)
Pages (from-to)5245-5273
Number of pages29
JournalPhysics in medicine and biology
Issue number16
StatePublished - Aug 21 2012

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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