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This article provides an introduction to nuclear magnetic resonance spectroscopy in pulsed magnetic fields (PFNMR), focusing on its capabilities, applications, and future developments in research involving high magnetic fields. It…

Strongly Correlated Electrons · Physics 2025-03-07 H. Kühne , Y. Ihara

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu

An accurate treatment of electronic spectra in large systems with a technique such as time dependent density functional theory (TDDFT) is computationally challenging. Due to the Nyquist sampling theorem, direct real time simulations must be…

Materials Science · Physics 2024-01-17 Matthias Kick , Ezra Alexander , Anton Beiersdorfer , Troy Van Voorhis

The non-uniform sampling is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partial sampled exponentials is highly expected in general signal processing and…

Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are relatively slow, even with parallel imaging. Incoherent…

Image and Video Processing · Electrical Eng. & Systems 2021-07-20 Yang Gao , Martijn Cloos , Feng Liu , Stuart Crozier , G. Bruce Pike , Hongfu Sun

Deep denoising models require extensive real-world training data, which is challenging to acquire. Current noise synthesis techniques struggle to accurately model complex noise distributions. We propose a novel Realistic Noise Synthesis…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Qi Wu , Mingyan Han , Ting Jiang , Chengzhi Jiang , Jinting Luo , Man Jiang , Haoqiang Fan , Shuaicheng Liu

Magnetic resonance imaging (MRI) plays a vital role in clinical diagnostics, yet it remains hindered by long acquisition times and motion artifacts. Multi-contrast MRI reconstruction has emerged as a promising direction by leveraging…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Xinming Fang , Chaoyan Huang , Juncheng Li , Jun Wang , Jun Shi , Guixu Zhang

Two-dimensional Nuclear Magnetic Resonance (NMR) is essential in molecular structure determination. The Nitrogen-Vacancy (NV) center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In…

Long scan time significantly hinders the widespread applications of three-dimensional multi-contrast cardiac magnetic resonance (3D-MC-CMR) imaging. This study aims to accelerate 3D-MC-CMR acquisition by a novel method based on score-based…

Signal Processing · Electrical Eng. & Systems 2024-10-29 Yuanyuan Liu , Zhuo-Xu Cui , Shucong Qin , Congcong Liu , Hairong Zheng , Haifeng Wang , Yihang Zhou , Dong Liang , Yanjie Zhu

In portable, three dimensional, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high quality images from a limited number of radio-frequency (RF) measurements due to receiver (Rx) or…

Computer Vision and Pattern Recognition · Computer Science 2018-08-08 Yeo Hun Yoon , Shujaat Khan , Jaeyoung Huh , Jong Chul Ye

Diffusion models achieve state-of-the-art generative performance but suffer from high computational costs during inference due to the repeated evaluation of a heavy neural network. In this work, we propose Dual-Rate Diffusion, a method to…

Machine Learning · Computer Science 2026-05-19 Grigory Bartosh , David Ruhe , Emiel Hoogeboom , Jonathan Heek , Thomas Mensink , Tim Salimans

In vivo H nuclear magnetic resonance (NMR) spectroscopy is an important tool for performing non-invasive quantitative assessments of brain tumour glucose metabolism. Brain tumours are considered fast-growth tumours because of their high…

Biological Physics · Physics 2010-10-15 Alejandro Chinea Manrique de Lara

One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterization, and metabolomics, yet its interpretation remains heavily…

While energy-based models (EBMs) exhibit a number of desirable properties, training and sampling on high-dimensional datasets remains challenging. Inspired by recent progress on diffusion probabilistic models, we present a diffusion…

Machine Learning · Computer Science 2021-03-30 Ruiqi Gao , Yang Song , Ben Poole , Ying Nian Wu , Diederik P. Kingma

Recent progress in the application of color centers to nanoscale spin sensing makes the combined use of noise spectroscopy and scanning probe imaging an attractive route for the characterization of arbitrary material systems. Unfortunately,…

Diffusion magnetic resonance imaging (dMRI) enables non-invasive investigation of tissue microstructure. The Standard Model (SM) of white matter aims to disentangle dMRI signal contributions from intra- and extra-axonal water compartments.…

Image and Video Processing · Electrical Eng. & Systems 2026-04-15 Tom Hendriks , Gerrit Arends , Edwin Versteeg , Anna Vilanova , Maxime Chamberland , Chantal M. W. Tax

Achieving accurate material segmentation for 3-channel RGB images is challenging due to the considerable variation in a material's appearance. Hyperspectral images, which are sets of spectral measurements sampled at multiple wavelengths,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yuwen Heng , Yihong Wu , Jiawen Chen , Srinandan Dasmahapatra , Hansung Kim

Magnetic resonance imaging (MRI), especially functional MRI (fMRI) and diffusion MRI (dMRI), is essential for studying neurodegenerative diseases. However, missing modalities pose a major barrier to their clinical use. Although GAN- and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Xiongri Shen , Jiaqi Wang , Yi Zhong , Zhenxi Song , Leilei Zhao , Yichen Wei , Lingyan Liang , Shuqiang Wang , Baiying Lei , Demao Deng , Zhiguo Zhang

Ferromagnetic resonance (FMR) spectroscopy is a powerful method for quantifying internal magnetic anisotropy fields in nanoparticles, which is important in a wide range of biomedical and storage applications. The interpretation of FMR…

Materials Science · Physics 2022-06-02 David Slay , Michalis Charilaou

Nuclear magnetic resonance (NMR) is a powerful method for determining the structure of molecules and proteins. While conventional NMR requires averaging over large ensembles, recent progress with single-spin quantum sensors has created the…