X-ray computed tomography (CT) iterative image reconstruction from sparse-view projection data has been an important research topic for radiation reduction in clinic. In this paper, to relieve the requirement of misalignment reduction operation of the prior image constrained compressed sensing (PICCS) approach introduced by Chen et al, we present an iterative image reconstruction approach for s...

Iterative Algorithms can obtain good reconstruction image for enough Iterative times in the technique ct image reconstruction. The order method of the Weighted Distance Orthogonal (WDO) is introduced in this paper to accelerate the Iterative reconstruction, which improves greatly the access mode of ART to projection data, based on the crucial effect that the access order of projection date has ...

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The application of diffuse optical tomography (DOT) methods for neuroimaging of humans is challenging due to the geometry of each individual subject and light level constraints. A high density imaging array system has been developed and used to demonstrate the possibility of true tomographic reconstruction of cortical activity within the adult subjects which are consistent with studies using fu...

Model based iterative reconstruction (MBIR) algorithms have recently been applied to computed tomography and demonstrated superior image quality. MBIR algorithms also have the potential to incorporate sophisticated models of data acquisition to address artifacts. In this paper, we introduce kinetic models to the MBIR framework, which allow voxel value to change as a function of time. Convention...

There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of x-ray CT imaging. IR has the ability to significantly reduce patient dose; it provides the flexibility to reconstruct images from arbitrary x-ray system geometries and allows one to include detailed models of photon transport and detection physics to accurately correct...

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Iterative image reconstruction algorithms have been widely used in the field of positron emission tomography (PET). However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations is high. In this paper, we propose a new algorithm to reconstruct an image from the PET emission projection data by using the conditional entropy ma...

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