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Open AccessJournal ArticleDOI

X-Ray Luminescence and X-Ray Fluorescence Computed Tomography: New Molecular Imaging Modalities

TLDR
This paper reviews the development of X-ray luminescence andX-ray fluorescence CT and their relative merits and includes current problems and future research directions and the role of these modalities in future molecular imaging applications.
Abstract
X-ray luminescence and X-ray fluorescence computed tomography (CT) are two emerging technologies in X-ray imaging that provide functional and molecular imaging capability. Both emission-type tomographic imaging modalities use external X-rays to stimulate secondary emissions, either light or secondary X-rays, which are then acquired for tomographic reconstruction. These modalities surpass the limits of sensitivity in current X-ray imaging and have the potential of enabling X-ray imaging to extract molecular imaging information. These new modalities also promise to break through the spatial resolution limits of other in vivo molecular imaging modalities. This paper reviews the development of X-ray luminescence and X-ray fluorescence CT and their relative merits. The discussion includes current problems and future research directions and the role of these modalities in future molecular imaging applications.

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Citations
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Proceedings ArticleDOI

Analysis of X-Ray Images with Image Processing Techniques: A Review

TL;DR: X-ray imaging technique is used to detect bone fractures and then the obtained image is processed by different image processing methods such as Computer Aided Diagnosis, Edge Detection, segmentation which are beneficial for technicians.
Patent

X-optogenetics / u-optogenetics

TL;DR: In this article, a system for performing optogenetics using X-rays or ultrasound waves is described, which can trigger changes in proteins that modulate membrane potentials in neuronal cells.
Journal ArticleDOI

Imaging of X-Ray-Excited Emissions from Quantum Dots and Biological Tissue in Whole Mouse.

TL;DR: The use of keV X-rays to excite emission from QDs and tissue represent novel biomedical imaging technologies, and exploit emerging QDs as optical probes for spatial-temporal molecular imaging at greater depth than previously possible.
Journal ArticleDOI

Spectral-resolved cone-beam X-ray luminescence computed tomography with principle component analysis.

TL;DR: Results of digital simulation and the phantom experiment illustrated that the proposed method was capable of resolving adjacent multiple probes accurately and had better performance than the common multispectral CB-XLCT with spectrum information priori.
Journal ArticleDOI

A robust elastic net-â 1 â 2 reconstruction method for x-ray luminescence computed tomography.

Abstract: OBJECTIVE: X-ray luminescence computed tomography (XLCT) has played a crucial role in pre-clinical research and effective diagnosis of disease. However, due to the ill-posed of the XLCT inverse problem, the generalization of reconstruction methods and the selection of appropriate regularization parameters are still challenging in practical applications. In this research, an robust Elastic net-L1L2 reconstruction method is proposed aiming to the challenge. APPROACH: Firstly, our approach consists of L1 and L2 regularization to enhance the sparsity and suppress the smoothness. Secondly, through optimal approximation of the optimization problem, double modification of Landweber algorithm is adopted to solve the Elastic net-L1L2 regulazation. Thirdly, drawing on the ideal of supervised learning, multi-parameter K-fold cross validation strategy is proposed to determin the optimal parameters adaptively. MAIN RESULTS: To evaluate the performance of the Elastic net-L1L2 method, numerical simulations, phantom and in vivo experiments were conducted. In these experiments, the Elastic net-L1L2 method achieved the minimum reconstruction error (with smallest location error (LE), fluorescent yield relative error (FYRE), normalized root-mean-square error (NRMSE)) and the best image reconstruction quality (with largest contrast-to-noise ratio (CNR) and Dice similarity) among all methods. The results demonstrated that Elastic net-L1L2 can obtain superior reconstruction performance in terms of location accuracy, dual source resolution, robustness and \emph{in vivo} practicability. SIGNIFICANCE: It is believed that this study will further benefit preclinical applications with a view to provide a more reliable reference for the later researches on XLCT.
References
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