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Material decomposition refers to using the energy dependence of material physical properties to differentiate materials in a sample, which is a very important application in computed tomography(CT). In propagation-based X-ray phase-contrast…

Medical Physics · Physics 2023-12-01 Suyu Liao , Huitao Zhang , Peng Zhang , Yining Zhu

A new method is developed for three-dimensional (3D) reconstruction of multi-material objects using propagation-based X-ray phase-contrast tomography (PB-CT) with phase retrieval via the contrast transfer function (CTF) formalism. The…

Medical Physics · Physics 2023-05-15 Darren A. Thompson , Yakov I. Nesterets , Konstantin M. Pavlov , Timur E. Gureyev

We propose two easy-to-implement fast algorithms based on moment-matching to compute the nonlocal potential $\varphi(\textbf{x})=(U\ast \rho)(\textbf{x})$ on bounded domain, where the kernel $U$ is singular at the origin and the density…

Numerical Analysis · Mathematics 2026-02-16 Xin Liu , Qinglin Tang , Yong Zhang

We reconstruct the dark matter density field from spatially overlapping spectroscopic and photometric redshift catalogs through a forward modelling approach. Instead of directly inferring the underlying density field, we find the best…

Cosmology and Nongalactic Astrophysics · Physics 2023-12-01 Benjamin Horowitz , Peter Melchior

Optical microscopy is an essential tool in biology and medicine. Imaging thin, yet non-flat objects in a single shot (without relying on more sophisticated sectioning setups) remains challenging as the shallow depth of field that comes with…

Image and Video Processing · Electrical Eng. & Systems 2020-10-14 Adrian Shajkofci , Michael Liebling

Purpose: To develop a framework to reconstruct large-scale volumetric dynamic MRI from rapid continuous and non-gated acquisitions, with applications to pulmonary and dynamic contrast enhanced (DCE) imaging. Theory and Methods: The problem…

We study the problem of recovering an unknown compactly-supported multivariate function from samples of its Fourier transform that are acquired nonuniformly, i.e. not necessarily on a uniform Cartesian grid. Reconstruction problems of this…

Numerical Analysis · Mathematics 2022-05-04 Ben Adcock , Milana Gataric , José Luis Romero

This paper addresses the problem of high-resolution Doppler blood flow estimation from an ultrafast sequence of ultrasound images. Formulating the separation of clutter and blood components as an inverse problem has been shown in the…

Image and Video Processing · Electrical Eng. & Systems 2020-07-13 Duong-Hung Pham , Adrian Basarab , Ilyess Zemmoura , Jean-Pierre Remenieras , Denis Kouame

Derivative compressive sampling (DCS) is a signal reconstruction method from measurements of the spatial gradient with sub-Nyquist sampling rate. Applications of DCS include optical image reconstruction, photometric stereo, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-11 Md Fazle Rabbi

In this paper, two 8-point multiplication-free DCT approximations based on the Chen's factorization are proposed and their fast algorithms are also derived. Both transformations are assessed in terms of computational cost, error energy, and…

Signal Processing · Electrical Eng. & Systems 2022-07-26 C. J. Tablada , T. L. T. da Silveira , R. J. Cintra , F. M. Bayer

We propose a k-space preconditioning formulation for accelerating the convergence of iterative Magnetic Resonance Imaging (MRI) reconstructions from non-uniformly sampled k-space data. Existing methods either use sampling density…

Medical Physics · Physics 2020-05-13 Frank Ong , Martin Uecker , Michael Lustig

Magnetic resonance Fingerprinting (MRF) is a relatively new multi-parametric quantitative imaging method that involves a two-step process: (i) reconstructing a series of time frames from highly-undersampled non-Cartesian spiral k-space data…

Image and Video Processing · Electrical Eng. & Systems 2021-07-20 Yilin Liu , Yong Chen , Pew-Thian Yap

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration…

Medical Physics · Physics 2017-11-03 Priya Aggarwal , Anubha Gupta

This paper presents a new deformable convolution-based video frame interpolation (VFI) method, using a coarse to fine 3D CNN to enhance the multi-flow prediction. This model first extracts spatio-temporal features at multiple scales using a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Duolikun Danier , Fan Zhang , David Bull

Large-scale density functional theory (DFT) calculations provide a powerful tool to investigate the atomic and electronic structure of materials with complex structures. This article reviews a large-scale DFT calculation method, the…

Materials Science · Physics 2022-08-31 Ayako Nakata , David R. Bowler , Tsuyoshi Miyazaki

Magnetic Resonance Imaging (MRI) is a widely used medical imaging modality boasting great soft tissue contrast without ionizing radiation, but unfortunately suffers from long acquisition times. Long scan times can lead to motion artifacts,…

Signal Processing · Electrical Eng. & Systems 2022-07-05 Brett Levac , Sidharth Kumar , Sofia Kardonik , Jonathan I. Tamir

The performance of multivariate kernel density estimation (KDE) depends strongly on the choice of bandwidth matrix. The high computational cost required for its estimation provides a big motivation to develop fast and accurate methods. One…

Computation · Statistics 2016-05-13 Artur Gramacki , Jarosław Gramacki

Numerical inspection of wide-angle (WA) or ultra-wide-angle (UWA) computer-generated holograms (CGH) is a computationally demanding task. To surpass this limitation, we propose a novel computational approach for fast and accurate WA-CGH…

Parallel imaging techniques reduce magnetic resonance imaging (MRI) scan time but image quality degrades as the acceleration factor increases. In clinical practice, conservative acceleration factors are chosen because no mechanism exists to…

Image and Video Processing · Electrical Eng. & Systems 2026-05-26 Ilias I. Giannakopoulos , Lokesh B Gautham Muthukumar , Yvonne W. Lui , Riccardo Lattanzi

Density functional theory (DFT) has been actively used and developed recently. DFT is an efficient instrument for describing a wide range of nanoscale phenomena: wetting transition, capillary condensation, adsorption, and others. In this…

Mesoscale and Nanoscale Physics · Physics 2020-07-21 Yuriy Kanygin