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Magnetic particle imaging (MPI) is an imaging modality exploiting the nonlinear magnetization behavior of (super-)paramagnetic nanoparticles to obtain a space- and often also time-dependent concentration of a tracer consisting of these…

图像与视频处理 · 电气工程与系统科学 2020-07-06 Sören Dittmer , Tobias Kluth , Mads Thorstein Roar Henriksen , Peter Maass

Magnetic Particle Imaging (MPI) is an emerging imaging modality based on the magnetic response of superparamagnetic iron oxide nanoparticles to achieve high-resolution and real-time imaging without harmful radiation. One key challenge in…

数值分析 · 数学 2025-01-13 Meira Iske , Hannes Albers , Tobias Knopp , Tobias Kluth

Magnetic Particle Imaging (MPI) is a recent imaging modality where superparamagnetic nanoparticles are employed as tracers. The reconstruction task is to obtain the spatial particle distribution from a voltage signal induced by the…

数值分析 · 数学 2025-08-11 Thomas März , Vladyslav Gapyak , Andreas Weinmann

Magnetic particle imaging (MPI) is a medical imaging modality of recent origin, and it exploits the nonlinear magnetization phenomenon to recover the spatially dependent concentration of the nanoparticles. Currently, image reconstruction in…

数值分析 · 数学 2019-04-23 Tobias Kluth , Bangti Jin

Magnetic particle imaging (MPI) offers exceptional contrast for magnetic nanoparticles (MNP) at high spatio-temporal resolution. A common procedure in MPI starts with a calibration scan to measure the system matrix (SM), which is then used…

图像与视频处理 · 电气工程与系统科学 2022-11-04 Alper Güngör , Baris Askin , Damla Alptekin Soydan , Emine Ulku Saritas , Can Barış Top , Tolga Çukur

Magnetic Particle Imaging (MPI) is a novel medical imaging modality. One of the established methods for MPI reconstruction is based on the System Matrix (SM). However, the calibration of the SM is often time-consuming and requires repeated…

计算机视觉与模式识别 · 计算机科学 2025-11-11 Xuqing Geng , Lei Su , Zhongwei Bian , Zewen Sun , Jiaxuan Wen , Jie Tian , Yang Du

Magnetic Particle Imaging (MPI) is a promising tomographic technique for visualizing the spatio-temporal distribution of superparamagnetic nanoparticles, with applications ranging from cancer detection to real-time cardiovascular…

计算机视觉与模式识别 · 计算机科学 2026-01-23 Vladyslav Gapyak , Thomas März , Andreas Weinmann

Magnetic particle imaging (MPI) is an emerging medical imaging modality which offers a unique combination of high temporal and spatial resolution, sensitivity and biocompatibility. For system-matrix (SM) based image reconstruction in MPI, a…

软件工程 · 计算机科学 2024-01-12 Anselm von Gladiss , Amir Shayan Ahmadian , Jan Jürjens

Magnetic Particle Imaging (MPI) is a tomographic imaging modality capable of real-time, high-sensitivity mapping of superparamagnetic iron oxide nanoparticles. Model-based image reconstruction provides an alternative to conventional methods…

Magnetic Particle Imaging (MPI) is an emerging imaging modality that maps the spatial distribution of magnetic nanoparticles. The x-space reconstruction in MPI results in highly blurry images, where the resolution depends on both system…

The ability of snapshot compressive imaging (SCI) systems to efficiently capture high-dimensional (HD) data has led to an inverse problem, which consists of recovering the HD signal from the compressed and noisy measurement. While…

图像与视频处理 · 电气工程与系统科学 2023-03-01 Yaping Zhao , Siming Zheng , Xin Yuan

Magnetic Particle Imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than…

Purpose: To develop a general framework for Parallel Imaging (PI) with the use of Maxwell regularization for the estimation of the sensitivity maps (SMs) and constrained optimization for the parameter-free image reconstruction. Theory and…

图像与视频处理 · 电气工程与系统科学 2020-08-21 Matteo Alessandro Francavilla , Stamatios Lefkimmiatis , Jorge F. Villena , Athanasios G. Polimeridis

Magnetic particle imaging (MPI) is a relatively new imaging modality. The nonlinear magnetization behavior of nanoparticles in an applied magnetic field is employed to reconstruct an image of the concentration of nanoparticles. Finding a…

应用物理 · 物理学 2018-07-04 Tobias Kluth

The image reconstruction problem of the tomographic imaging technique magnetic particle imaging (MPI) requires the solution of a linear inverse problem. One prerequisite for this task is that the imaging operator that describes the mapping…

计算物理 · 物理学 2019-07-12 Tobias Kluth , Patryk Szwargulski , Tobias Knopp

Magnetic Particle Imaging (MPI) is a promising tracer-based, functional medical imaging technique which measures the non-linear magnetization response of magnetic nanoparticles to a dynamic magnetic field. For image reconstruction, system…

图像与视频处理 · 电气工程与系统科学 2021-08-26 Christina Brandt , Christiane Schmidt

Magnetic particle imaging (MPI) is an imaging method that can visualize magnetic nanoparticles in positive contrast, without radiation exposure. Recently, we proposed an image reconstruction method for projection-based MPI (pMPI), in which…

医学物理 · 物理学 2023-05-01 Kenya Murase

Magnetic Particle Imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio-temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an…

数值分析 · 数学 2021-09-15 Florian Lieb , Tobias Knopp

Quantitative Magnetic Resonance Imaging (qMRI) enables the reproducible measurement of biophysical parameters in tissue. The challenge lies in solving a nonlinear, ill-posed inverse problem to obtain the desired tissue parameter maps from…

图像与视频处理 · 电气工程与系统科学 2024-05-08 Felix F Zimmermann , Christoph Kolbitsch , Patrick Schuenke , Andreas Kofler

Deep equilibrium models (DEQ) have emerged as a powerful alternative to deep unfolding (DU) for image reconstruction. DEQ models-implicit neural networks with effectively infinite number of layers-were shown to achieve state-of-the-art…

图像与视频处理 · 电气工程与系统科学 2022-10-11 Weijie Gan , Chunwei Ying , Parna Eshraghi , Tongyao Wang , Cihat Eldeniz , Yuyang Hu , Jiaming Liu , Yasheng Chen , Hongyu An , Ulugbek S. Kamilov
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