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Diffusion models have emerged as powerful priors for solving inverse problems in computed tomography (CT). In certain applications, such as neutron CT, it can be expensive to collect large amounts of measurements even for a single scan,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Timofey Efimov , Singanallur Venkatakrishnan , Maliha Hossain , Haley Duba-Sullivan , Amirkoushyar Ziabari

The low-density imaging performance of a zone plate based nano-resolution hard X-ray computed tomography (CT) system can be significantly improved by incorporating a grating-based Lau interferometer. Due to the diffraction, however, the…

Image and Video Processing · Electrical Eng. & Systems 2023-10-16 Xuebao Cai , Yuhang Tan , Ting Su , Dong Liang , Hairong Zheng , Jinyou Xu , Peiping Zhu , Yongshuai Ge

X-ray imaging, traditionally relying on attenuation contrast, struggles to differentiate materials with similar attenuation coefficients like soft tissues. X-ray phase contrast imaging (XPCI) and dark-field (DF) imaging provide enhanced…

Medical Physics · Physics 2025-06-05 Jingcheng Yuan , Mini Das

When x-rays penetrate soft matter, their phase changes more rapidly than their amplitude. In- terference effects visible with high brightness sources creates higher contrast, edge enhanced images. When the object is piecewise smooth (made…

In this paper, we investigate image reconstruction for dynamic Computed Tomography. The motion of the target with respect to the measurement acquisition rate leads to highly resolved in time but highly undersampled in space measurements.…

Image and Video Processing · Electrical Eng. & Systems 2025-06-27 Pablo Arratia , Matthias Ehrhardt , Lisa Kreusser

This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate. Such systems pose a challenge for iterative image…

Medical Physics · Physics 2016-11-17 Emil Y. Sidky , Rick Chartrand , Yuval Duchin , Christer Ullberg , Xiaochuan Pan

The inverse problem we consider is to reconstruct the location and shape of buried obstacles in the lower half-space of an unbounded two-layered medium in two dimensions from phaseless far-field data. A main difficulty of this problem is…

Numerical Analysis · Mathematics 2021-05-26 Long Li , Jiansheng Yang , Bo Zhang , Haiwen Zhang

The recovery of images from the observations that are degraded by a linear operator and further corrupted by Poisson noise is an important task in modern imaging applications such as astronomical and biomedical ones. Gradient-based…

Computer Vision and Pattern Recognition · Computer Science 2015-03-17 Dai-Qiang Chen

Most methods tackling the phase retrieval problem of magnitude-only antenna measurements suffer from unrealistic sampling requirements, from unfeasible computational complexities, and, most severely, from the lacking reliability of…

Signal Processing · Electrical Eng. & Systems 2022-02-01 Alexander Paulus , Josef Knapp , Jonas Kornprobst , Thomas F. Eibert

Building on the well-known total-variation (TV), this paper develops a general regularization technique based on nonlinear isotropic diffusion (NID) for inverse problems with piecewise smooth solutions. The novelty of our approach is to be…

Numerical Analysis · Mathematics 2021-08-25 Bernadette N. Hahn , Gael Rigaud , Richard Schmähl

In this work, we propose a new paradigm of iterative model-based reconstruction algorithms for providing real-time solution for zooming-in and refining a region of interest in medical and clinical tomographic images. This algorithmic…

Image and Video Processing · Electrical Eng. & Systems 2025-12-01 Junqi Tang , Guixian Xu , Jinglai Li

This paper is concerned with the inverse problem of reconstructing an inhomogeneous medium from the acoustic far-field data at a fixed frequency in two dimensions. This inverse problem is severely ill-posed (and also strongly nonlinear),…

Numerical Analysis · Mathematics 2023-09-21 Kai Li , Bo Zhang , Haiwen Zhang

This paper presents a novel approach on solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method, which allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for…

This revisit gives a survey on the analytical methods for the inverse exponential Radon transform which has been investigated in the past three decades from both mathematical interests and medical applications such as nuclear medicine…

Image and Video Processing · Electrical Eng. & Systems 2020-02-06 Jason You

We consider the inexact Newton methods $$ x_{n+1}^\d=x_n^\d-g_{\a_n}(F'(x_n^\d)^* F'(x_n^\d)) F'(x_n^\d)^* (F(x_n^\d)-y^\d) $$ for solving nonlinear ill-posed inverse problems $F(x)=y$ using the only available noise data $y^\d$ satisfying…

Numerical Analysis · Mathematics 2010-10-19 Qinian Jin

We consider the variational reconstruction framework for inverse problems and propose to learn a data-adaptive input-convex neural network (ICNN) as the regularization functional. The ICNN-based convex regularizer is trained adversarially…

In recent years, a novel x-ray imaging modality has emerged that reveals unresolved sample microstructure via a "dark-field image", which provides complementary information to conventional "bright-field" images, such as attenuation and…

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A…

Optimization and Control · Mathematics 2019-06-10 Huibin Chang , Pable Enfedaque , Stefano Marchesini

In many models in condensed matter physics and high-energy physics, one finds inhomogeneous phases at high density and low temperature. These phases are characterized by a spatially dependent condensate or order parameter. A proper…

High Energy Physics - Phenomenology · Physics 2017-08-03 Prabal Adhikari , Jens O. Andersen

We study Newton type methods for inverse problems described by nonlinear operator equations $F(u)=g$ in Banach spaces where the Newton equations $F'(u_n;u_{n+1}-u_n) = g-F(u_n)$ are regularized variationally using a general data misfit…

Numerical Analysis · Mathematics 2015-04-01 Thorsten Hohage , Frank Werner
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