A5102997961- Medical Imaging Techniques and Applications
- Advanced X-ray Imaging Techniques
- Advanced X-ray and CT Imaging
- Granular flow and fluidized beds
- Mineral Processing and Grinding
- Electrical and Bioimpedance Tomography
- Advanced MRI Techniques and Applications
- Seismic Imaging and Inversion Techniques
- Digital Holography and Microscopy
- Optical measurement and interference techniques
- Advanced Electron Microscopy Techniques and Applications
- Groundwater flow and contamination studies
- Seismology and Earthquake Studies
- Seismic Waves and Analysis
- Calcium Carbonate Crystallization and Inhibition
- Ocular and Laser Science Research
- Geological and Geochemical Analysis
- Electron and X-Ray Spectroscopy Techniques
- Photoacoustic and Ultrasonic Imaging
- Enhanced Oil Recovery Techniques
- Paleontology and Stratigraphy of Fossils
- Particle Detector Development and Performance
- Infrared Thermography in Medicine
- Fluid Dynamics and Mixing
- Drilling and Well Engineering
Deutsches Elektronen-Synchrotron DESY
2019-2024
Brookhaven National Laboratory
2023-2024
Xi'an High Tech University
2020
Argonne National Laboratory
2002-2018
Delft University of Technology
2013-2015
Abstract Synchrotron-based X-ray tomography offers the potential for rapid large-scale reconstructions of interiors materials and biological tissue at fine resolution. However, radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times reducing signals with shorter times. We present a deep convolutional neural network (CNN) method that increases acquired tomographic signal by least factor 10 low-dose fast improving quality...
This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The uses generative adversarial network (GAN) to solve the inverse of Radon transform directly. It works independent sinograms without additional training steps. GAN has been developed fit input sinogram with model generated from predicted reconstruction. Good quality reconstructions can be obtained during minimization fitting errors. is self-training procedure based on physics model, instead data. showed...
Nucleation of barite (BaSO4) has broad implications in geological, environmental, and materials sciences. While impurity metals are common, our understanding how they impact nucleation remains dim. Here, we used classical optical microscopy compared to fast X-ray nanotomography (XnT) investigate heterogeneous on silica situ with Sr2+ as an ion. The observed rates were consistent theory (CNT), where crystals displayed a nonuniform size distribution, exhibiting distinct morphologies incubation...
Two in situ `nanoreactors' for high-resolution imaging of catalysts have been designed and applied at the hard X-ray nanoprobe endstation beamline P06 PETRA III synchrotron radiation source. The reactors house samples supported on commercial MEMS chips, were complementary ptychography (23 nm spatial resolution) transmission electron microscopy, with additional fluorescence measurements. allow pressures 100 kPa temperatures up to 1573 K, offering a wide range conditions relevant catalysis....
This study presents a deep learning algorithm for solving the inverse problem of phase retrieval in optical near-field (Fresnel) regime using single intensity measurement (in-line hologram). The was developed self-learning fashion based on generative adversarial networks (GANs) tomographic reconstruction (GANrec). In this paper, original GANrec is adapted to solve problem. From hologram, can recover both and amplitude unpropagated exit wave field. Compared with other state-of-the-art...
In this article, we introduce three different strategies of tomographic reconstruction based on deep learning. These algorithms are model-based learning for iterative optimization. We discuss the basic principles developing these algorithms. The performance them is analyzed and evaluated both theory simulation reconstruction. developed open-source software to run in same framework. From results, all showed improvements quality accuracy where strategy Generative Adversarial Networks advantage...
This study presents a deep learning algorithm for solving the inverse problem of phase retrieval in optical near-field (Fresnel) regime using single intensity measurement (in-line hologram). The was developed self-learning fashion based on generative adversarial networks (GANs) tomographic reconstruction (GANrec). In this paper, original GANrec is adapted to solve problem. From hologram, can recover both and amplitude unpropagated exit wave field. Compared with other state-of-the-art...
Laser active imaging is widely used in many fields. The intensity image quality of laser affected by various degradations, such as speckle effect and noise. Most existing objective assessment (IQA) methods that consider only a single distorted are not suitable for an image. A multiscale full-reference IQA method presented. proposed based on improved gradient magnitude similarity deviation (GMSD) the nonsubsampled contourlet transform (NSCT) domain. reference images decomposed NSCT to emulate...
High energy linear colliders require very small beams at the interaction point to produce high luminosities, and these must be measured monitored. We have developed tested a technique where profile can obtained from an extension of pinhole camera optics using thick, single sided collimators slits. Very resolutions (a few nm) should possible. Gamma bremsstrahlung, Compton or beamstrahlung radiation. describe tests bremsstrahlung 800 MeV electron beam Bates/MIT, scattered photons 47 GeV Final...
X-ray tomography is a nondestructive technique that visualizes interior features in solid objects. To achieve given resolution, sufficient number of projection images over cycle required for 3D reconstruction based on the Crowther criterion. However, practical limitations such as geometrical constraints, data acquisition time, and low dose requirements often prohibit full dataset, only allowing limited angular range. The unsampled angles lead to 'missing edge' problem tomography, which...