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Related papers: Characterization of Metal Artifacts in X-ray Compu…

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The objective of this article is to study the behavior of electromagnetic field under X-ray diffraction by time-dependent deformed crystals. Derived system of differential equations looks like the Takagi equations in the case of…

Computational Physics · Physics 2007-05-23 Svetlana Sytova

X-ray fluorescence spectrometry (XRFS) was used as a multielement method of evaluation of individual whole human tooth or tooth tissues for their amounts of trace elements. Measurements were carried out on human enamel, dentine, and dental…

Improvements in X-ray optics critically depend on the measurement of their optical performance. The knowledge of wavefront aberrations, for example, can be used to improve the fabrication of optical elements or to design phase correctors to…

We show how the coupling between the phonons and electrons in a strongly correlated metal can result in phonon frequencies which have a non-monotonic temperature dependence. Dynamical mean-field theory is used to study the Hubbard-Holstein…

Strongly Correlated Electrons · Physics 2009-10-31 J. Merino , Ross H. McKenzie

Segmentation of very large images is a common problem in microscopy, medical imaging or remote sensing. The problem is usually addressed by sliding window inference, which can theoretically lead to seamlessly stitched predictions. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Elena Buglakova , Anwai Archit , Edoardo D'Imprima , Julia Mahamid , Constantin Pape , Anna Kreshuk

This study investigates the effects of radio-opaque artefacts, such as skin markers, breast implants, and pacemakers, on mammography classification models. After manually annotating 22,012 mammograms from the publicly available EMBED…

Image and Video Processing · Electrical Eng. & Systems 2025-05-27 Amelia Schueppert , Ben Glocker , Mélanie Roschewitz

Crystal property prediction, governed by quantum mechanical principles, is computationally prohibitive to solve exactly for large many-body systems using traditional density functional theory. While machine learning models have emerged as…

Materials Science · Physics 2026-01-28 Bin Cao , Yang Liu , Longhan Zhang , Yifan Wu , Zhixun Li , Yuyu Luo , Hong Cheng , Yang Ren , Tong-Yi Zhang

The complex atomic structures and defects of metal-oxide surfaces are vital for a variety of applications in material science and chemistry. While scanning probe microscopy allows accessing atomic-scale structures in real space, elemental…

The Radon cumulative distribution transform (R-CDT) exploits one-dimensional Wasserstein transport and the Radon transform to represent prominent features in images. It is closely related to the sliced Wasserstein distance and facilitates…

Numerical Analysis · Mathematics 2026-02-02 Matthias Beckmann , Robert Beinert , Jonas Bresch

The appraisal of metallic materials requires application of advanced characterisation techniques. In this paper, the use has been made of Scanning Electron Microscopy, Transmission Electron Microscopy, X-ray diffraction (XRD) and Energy…

Materials Science · Physics 2016-10-27 David N. Githinji

In computed tomography (CT), the forward model consists of a linear Radon transform followed by an exponential nonlinearity based on the attenuation of light according to the Beer-Lambert Law. Conventional reconstruction often involves…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Sara Fridovich-Keil , Fabrizio Valdivia , Gordon Wetzstein , Benjamin Recht , Mahdi Soltanolkotabi

Over past decades, high energy X-ray diffraction techniques at synchrotron beamline offer us the unique possibility to follow concomitantly some mechanisms on the grain level in metallic materials. Crystal rotation, as one important factor…

Materials Science · Physics 2024-05-07 Zhida Liang , Emad Maawad , Florian Pyczak

The existence of metallic implants in projection images for cone-beam computed tomography (CBCT) introduces undesired artifacts which degrade the quality of reconstructed images. In order to reduce metal artifacts, projection inpainting is…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Fuxin Fan , Yangkong Wang , Ludwig Ritschl , Ramyar Biniazan , Marcel Beister , Björn Kreher , Yixing Huang , Steffen Kappler , Andreas Maier

We report on the formation of topological defects emerging from the cycloidal antiferromagnetic order at the surface of bulk BiFeO$_3$ crystals. Combining reciprocal and real-space magnetic imaging techniques, we first observe, in a single…

Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image-guided radiation therapy, implant dentistry or…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Mohammadreza Amirian , Daniel Barco , Ivo Herzig , Frank-Peter Schilling

Metal artifact reduction (MAR) is one of the most important research topics in computed tomography (CT). With the advance of deep learning technology for image reconstruction,various deep learning methods have been also suggested for metal…

Image and Video Processing · Electrical Eng. & Systems 2020-07-08 Junghyun Lee , Jawook Gu , Jong Chul Ye

Industry standards require medical device manufacturers to perform implant-induced artefact testing in phantoms at a pre-clinical stage to define the extent of artefacts that can be expected during MRI. Once a device is commercially…

Medical Physics · Physics 2023-06-19 Guy Fierens , Joris Walraevens , Ronald Peeters , Christ Glorieux , Nicolas Verhaert

Metal artefacts in CT images may disrupt image quality and interfere with diagnosis. Recently many deep-learning-based CT metal artefact reduction (MAR) methods have been proposed. Current deep MAR methods may be troubled with domain gap…

Computer Vision and Pattern Recognition · Computer Science 2021-11-29 Muge Du , Kaichao Liang , Yinong Liu , Yuxiang Xing

X-ray spectroscopy is one of the most powerful tools to access structure and properties of matter in different states of aggregation as it allows to trace atomic and molecular energy levels in course of various physical and chemical…

Chemical Physics · Physics 2019-06-12 Sergey I. Bokarev , Oliver Kühn

Plastic deformation of micron-scale crystalline solids exhibits stress-strain curves with significant sample-to-sample variations. It is a pertinent question if this variability is purely random or to some extent predictable. Here we show,…

Disordered Systems and Neural Networks · Physics 2020-01-31 Henri Salmenjoki , Mikko J. Alava , Lasse Laurson
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