Compressed sensing with gradient total variation for low-dose CBCT reconstruction

Chang Woo Seo, Bo Kyung Cha, Seongchae Jeon, Young Huh, Justin C. Park, Byeonghun Lee, Junghee Baek, Eunyoung Kim

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This paper describes the improvement of convergence speed with gradient total variation (GTV) in compressed sensing (CS) for low-dose cone-beam computed tomography (CBCT) reconstruction. We derive a fast algorithm for the constrained total variation (TV)-based a minimum number of noisy projections. To achieve this task we combine the GTV with a TV-norm regularization term to promote an accelerated sparsity in the X-ray attenuation characteristics of the human body. The GTV is derived from a TV and enforces more efficient computationally and faster in convergence until a desired solution is achieved. The numerical algorithm is simple and derives relatively fast convergence. We apply a gradient projection algorithm that seeks a solution iteratively in the direction of the projected gradient while enforcing a non-negatively of the found solution. In comparison with the Feldkamp, Davis, and Kress (FDK) and conventional TV algorithms, the proposed GTV algorithm showed convergence in ≤18 iterations, whereas the original TV algorithm needs at least 34 iterations in reducing 50% of the projections compared with the FDK algorithm in order to reconstruct the chest phantom images. Future investigation includes improving imaging quality, particularly regarding X-ray cone-beam scatter, and motion artifacts of CBCT reconstruction.

Original languageEnglish (US)
Pages (from-to)570-573
Number of pages4
JournalNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
StatePublished - Jun 1 2015
Externally publishedYes


  • Iterative reconstruction Compressed sensing Total variation Gradient total variation Low-dose CBCT

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Instrumentation


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