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Title: TV-based conjugate gradient method and discrete L-curve for few-view CT reconstruction of X-ray in vivo data

High-resolution, three-dimensional (3D) imaging of soft tissues requires the solution of two inverse problems: phase retrieval and the reconstruction of the 3D image from a tomographic stack of two-dimensional (2D) projections. The number of projections per stack should be small to accommodate fast tomography of rapid processes and to constrain X-ray radiation dose to optimal levels to either increase the duration of in vivo time-lapse series at a given goal for spatial resolution and/or the conservation of structure under X-ray irradiation. In pursuing the 3D reconstruction problem in the sense of compressive sampling theory, we propose to reduce the number of projections by applying an advanced algebraic technique subject to the minimisation of the total variation (TV) in the reconstructed slice. This problem is formulated in a Lagrangian multiplier fashion with the parameter value determined by appealing to a discrete L-curve in conjunction with a conjugate gradient method. The usefulness of this reconstruction modality is demonstrated for simulated and in vivo data, the latter acquired in parallel-beam imaging experiments using synchrotron radiation. (C) 2015 Optical Society of America
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Publication Date:
OSTI Identifier:
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Optics Express; Journal Volume: 23; Journal Issue: 5
Optical Society of America (OSA)
Research Org:
Argonne National Laboratory (ANL)
Sponsoring Org:
China Scholarship Council; German Federal Ministry of Education and Research (BMBF); Karlsruhe Institute of Technology; USDOE Office of Science - Office of Basic Energy Sciences
Country of Publication:
United States