To maximize the time-integrated X-ray flux from multiple X-ray sources and shorten the data acquisition process, a promising way is to allow overlapped projections from multiple sources being simultaneously on without involving the source multiplexing technology. The most challenging task in this configuration is to perform image reconstruction effectively and efficiently from overlapped projections. Inspired by the single-source simultaneous algebraic reconstruction technique (SART), we hereby develop a multisource SART-type reconstruction algorithm regularized by a sparsity-oriented constraint in the soft-threshold filtering framework to reconstruct images from overlapped projections. Our numerical simulation results verify the correctnes...
[[abstract]]The authors develop a projection operator that simultaneously projects onto the set of a...
In many transmission imaging geometries, the transmitted "beams" of photons overlap on the detector,...
International audienceWe propose a variational approach for simultaneous reconstruction and multicla...
Based on the recent mathematical findings on solving the linear inverse problems with sparsity const...
3D image reconstruction from a set of X-ray projections is an important image reconstruction problem...
Current computed tomography (CT) scanners, including micro-CT scanners, utilize a point x-ray source...
The key idea discussed in this paper is to reconstruct an image from overlapped projections so that ...
Abstract—Computed tomography (CT) has been extensively studied for years and widely used in the mode...
In 1984, the simultaneous algebraic reconstruction technique (SART) was developed as a major refinem...
In 1984, the simultaneous algebraic reconstruction technique (SART) was developed as a major refinem...
This paper describes a technique for restoring and reconstructing a scene from overlapping images. I...
Simultaneous algebraic reconstruction technique (SART) [1, 2] is an iterative method for solving inv...
Compressed sensing is a powerful mathematical modelling tool to recover sparse signals from undersam...
In many transmission imaging geometries, the transmitted “beams” of photons overlap on the detector,...
International audienceIterative reconstruction methods are used in X-ray Computed Tomography in orde...
[[abstract]]The authors develop a projection operator that simultaneously projects onto the set of a...
In many transmission imaging geometries, the transmitted "beams" of photons overlap on the detector,...
International audienceWe propose a variational approach for simultaneous reconstruction and multicla...
Based on the recent mathematical findings on solving the linear inverse problems with sparsity const...
3D image reconstruction from a set of X-ray projections is an important image reconstruction problem...
Current computed tomography (CT) scanners, including micro-CT scanners, utilize a point x-ray source...
The key idea discussed in this paper is to reconstruct an image from overlapped projections so that ...
Abstract—Computed tomography (CT) has been extensively studied for years and widely used in the mode...
In 1984, the simultaneous algebraic reconstruction technique (SART) was developed as a major refinem...
In 1984, the simultaneous algebraic reconstruction technique (SART) was developed as a major refinem...
This paper describes a technique for restoring and reconstructing a scene from overlapping images. I...
Simultaneous algebraic reconstruction technique (SART) [1, 2] is an iterative method for solving inv...
Compressed sensing is a powerful mathematical modelling tool to recover sparse signals from undersam...
In many transmission imaging geometries, the transmitted “beams” of photons overlap on the detector,...
International audienceIterative reconstruction methods are used in X-ray Computed Tomography in orde...
[[abstract]]The authors develop a projection operator that simultaneously projects onto the set of a...
In many transmission imaging geometries, the transmitted "beams" of photons overlap on the detector,...
International audienceWe propose a variational approach for simultaneous reconstruction and multicla...