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Diffusion models have recently gained popularity for accelerated MRI reconstruction due to their high sample quality. They can effectively serve as rich data priors while incorporating the forward model flexibly at inference time, and they…

Image and Video Processing · Electrical Eng. & Systems 2023-10-20 Batu Ozturkler , Chao Liu , Benjamin Eckart , Morteza Mardani , Jiaming Song , Jan Kautz

In porous material research, one main interest of nuclear magnetic resonance (NMR) diffusion experiments is the determination of the exact shape of pores. It has been a longstanding ques-tion if this is achievable in principle. In this…

Medical Physics · Physics 2012-05-09 Tristan Anselm Kuder , Frederik Bernd Laun

Element-specific spectroscopies using synchrotron-radiation can provide unique insights into materials properties. The recently developed technique of X-ray detected ferromagnetic resonance (XFMR) allows studying the magnetization dynamics…

Materials Science · Physics 2023-05-17 Gerrit van der Laan , Thorsten Hesjedal

We demonstrate an experimental method for direct 2D and 3D imaging of magnetic radio-frequency (rf) field distribution in metal-dielectric structures based on traveling wave (TW) magnetic resonance imaging (MRI) at ultra-high field (> 7T).…

Instrumentation and Detectors · Physics 2016-01-19 A. Tonyushkin , D. K. Deelchand , P. -F. Van de Moortele , G. Adriany , A. Kiruluta

Current deep learning approaches for diffusion MRI modeling circumvent the need for densely-sampled diffusion-weighted images (DWIs) by directly predicting microstructural indices from sparsely-sampled DWIs. However, they implicitly make…

Image and Video Processing · Electrical Eng. & Systems 2021-06-25 Mengwei Ren , Heejong Kim , Neel Dey , Guido Gerig

We review how a magnetic resonance force microscope (MRFM) can be applied to perform ferromagnetic resonance (FMR) spectroscopy of \emph{individual} sub-micron size samples. We restrict our attention to a thorough study of the spin-wave…

Diffusion models are typically trained using pointwise reconstruction objectives that are agnostic to the spectral and multi-scale structure of natural signals. We propose a loss-level spectral regularization framework that augments…

Machine Learning · Computer Science 2026-03-04 Satish Chandran , Nicolas Roque dos Santos , Yunshu Wu , Greg Ver Steeg , Evangelos Papalexakis

The frequency difference between two oppositely propagating spin waves can be used to probe several interesting magnetic properties, such as the Dzyaloshinkii-Moriya interaction (DMI). Propagating spin wave spectroscopy is a technique that…

Diagnosing Major Depressive Disorder (MDD) from functional magnetic resonance imaging (fMRI) using functional connectivity (FC) analysis requires large amounts of labeled data that are scarce in clinical settings. Existing augmentation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Muhammad Asif Hasan , Yanming Zhu , Xuefei Yin , Alan Wee-Chung Liew

Microstructure reconstruction has been an essential part of computational material engineering to reveal the relationship between microstructures and material properties. However, finding a general solution for microstructure…

Materials Science · Physics 2023-01-24 Kang-Hyun Lee , Gun Jin Yun

The determination of material parameters is significantly important in material science, which is often a challenging task. Recently, advancements have shown that magnetic parameters, such as the Dzyaloshinskii-Moriya interaction (DMI), can…

Materials Science · Physics 2024-08-23 Akito Watanabe , Yoshinobu Nakatani , Hiroyuki Awano , Kenji Tanabe

Mammography screening for early detection of breast lesions currently suffers from high amounts of false positive findings, which result in unnecessary invasive biopsies. Diffusion-weighted MR images (DWI) can help to reduce many of these…

Perfusion-weighted magnetic resonance imaging (MRI) is an imaging technique that allows one to measure tissue perfusion in an organ of interest through the injection of an intravascular paramagnetic contrast agent (CA). Due to a preference…

Computer Vision and Pattern Recognition · Computer Science 2017-08-28 Cagdas Ulas , Christine Preibisch , Jonathan Sperl , Thomas Pyka , Jayashree Kalpathy-Cramer , Bjoern Menze

Reconstructing high-fidelity magnetic resonance (MR) images from under-sampled k-space is a commonly used strategy to reduce scan time. The posterior sampling of diffusion models based on the real measurement data holds significant promise…

Image and Video Processing · Electrical Eng. & Systems 2024-07-04 Jiayue Chu , Chenhe Du , Xiyue Lin , Yuyao Zhang , Hongjiang Wei

Axon diameter and myelin thickness affect the conduction velocity of action potentials in the nervous system. Imaging them non-invasively with MRI-based methods is thus valuable for studying brain microstructure and function. Electron…

Diffusion-based image super-resolution methods have demonstrated significant advantages over GAN-based approaches, particularly in terms of perceptual quality. Building upon a lengthy Markov chain, diffusion-based methods possess remarkable…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Leheng Zhang , Weiyi You , Kexuan Shi , Shuhang Gu

Magnetic resonance (MR) imaging is commonly used in the clinical setting to non-invasively monitor the body. There exists a large variability in MR imaging due to differences in scanner hardware, software, and protocol design. Ideally, a…

Image and Video Processing · Electrical Eng. & Systems 2024-09-02 Savannah P. Hays , Samuel W. Remedios , Lianrui Zuo , Ellen M. Mowry , Scott D. Newsome , Peter A. Calabresi , Aaron Carass , Blake E. Dewey , Jerry L. Prince

Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric…

Diffusion MRI is a neuroimaging technique measuring the anatomical structure of tissues. Using diffusion MRI to construct the connections of tissues, known as fiber tracking, is one of the most important uses of diffusion MRI. Many…

Methodology · Statistics 2019-06-18 Zhou Lan , Brian J Reich