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Diffusion model is the most advanced method in image generation and has been successfully applied to MRI reconstruction. However, the existing methods do not consider the characteristics of multi-coil acquisition of MRI data. Therefore, we…

Image and Video Processing · Electrical Eng. & Systems 2022-12-23 Chentao Cao , Zhuo-Xu Cui , Jing Cheng , Sen Jia , Hairong Zheng , Dong Liang , Yanjie Zhu

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model. Volumetric scalar metrics including fractional anisotropy,…

Image and Video Processing · Electrical Eng. & Systems 2022-11-01 Zihao Tang , Xinyi Wang , Lihaowen Zhu , Mariano Cabezas , Dongnan Liu , Michael Barnett , Weidong Cai , Chengyu Wang

In recent years, diffusion models, and more generally score-based deep generative models, have achieved remarkable success in various applications, including image and audio generation. In this paper, we view diffusion models as an implicit…

Statistics Theory · Mathematics 2026-02-12 Hyeok Kyu Kwon , Dongha Kim , Ilsang Ohn , Minwoo Chae

We study perfusion by a multiscale model coupling diffusion in the tissue and diffusion along the one-dimensional segments representing the vasculature. We propose a block-diagonal preconditioner for the model equations and demonstrate its…

Analysis of PDEs · Mathematics 2018-03-14 Karl Erik Holter , Miroslav Kuchta , Kent-André Mardal

We propose ReMiDi, a novel method for inferring neuronal microstructure as arbitrary 3D meshes using a differentiable diffusion Magnetic Resonance Imaging (dMRI) simulator. We first implemented in PyTorch a differentiable dMRI simulator…

Image and Video Processing · Electrical Eng. & Systems 2025-03-03 Prathamesh Pradeep Khole , Zahra Kais Petiwala , Shri Prathaa Magesh , Ehsan Mirafzali , Utkarsh Gupta , Jing-Rebecca Li , Andrada Ianus , Razvan Marinescu

This study introduces a diffusion-based framework for robust and accurate segmenton of vertebrae, intervertebral discs (IVDs), and spinal canal from Magnetic Resonance Imaging~(MRI) scans of patients with low back pain (LBP), regardless of…

Image and Video Processing · Electrical Eng. & Systems 2024-11-20 Maria Monzon , Thomas Iff , Ender Konukoglu , Catherine R. Jutzeler

Deep learning analyses have offered sensitivity leaps in detection of cognitive states from functional MRI (fMRI) measurements across the brain. Yet, as deep models perform hierarchical nonlinear transformations on their input, interpreting…

Signal Processing · Electrical Eng. & Systems 2023-07-20 Hasan Atakan Bedel , Tolga Çukur

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

Diffusion MRI is a modern neuroimaging modality with a unique ability to acquire microstructural information by measuring water self-diffusion at the voxel level. However, it generates huge amounts of data, resulting from a large number of…

Image and Video Processing · Electrical Eng. & Systems 2023-04-06 Ikram Jumakulyyev , Thomas Schultz

Joint modeling of diffusion and relaxation has seen growing interest due to its potential to provide complementary information about tissue microstructure. For brain white matter, we designed an optimal diffusion-relaxometry MRI protocol…

Modelling the diffusion-relaxation magnetic resonance (MR) signal obtained from multi-parametric sequences has recently gained immense interest in the community due to new techniques significantly reducing data acquisition time. A preferred…

Medical Physics · Physics 2025-01-28 Fabian Bogusz , Tomasz Pieciak

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, which could introduce…

Image and Video Processing · Electrical Eng. & Systems 2023-04-04 Zhangxing Bian , Muhan Shao , Aaron Carass , Jerry L. Prince

Diffusion is a fundamental phenomenon that occurs ubiquitously in nature and remains the subject of continuous research interest. Understanding diffusion is a key to understanding leaving systems. In this Chapter, I discuss diffusion of…

Soft Condensed Matter · Physics 2018-10-15 Svyatoslav Kondrat

Purpose: Diffusion MRI (dMRI) provides a diverse set of quantitative measures and derived datatypes to assess white matter microstructure and macrostructure. Coupled with the increasing size of imaging studies using dMRI, the number of…

Diffusion models are important in tissue engineering as they enable an understanding of molecular delivery to cells in tissue constructs. As three-dimensional (3D) tissue constructs become larger, more intricate, and more clinically…

Tissues and Organs · Quantitative Biology 2015-12-22 Richard J. McMurtrey

We present a novel dual-encoded magnetization transfer (MT) and diffusion-weighted sequence and demonstrate its potential to resolve distinct properties of white matter fiber tracts at the sub-voxel level. The sequence was designed and…

Diffusion MRI (dMRI) provides a distinctive means to probe the microstructural architecture of living tissue, facilitating applications such as brain connectivity analysis, modeling across multiple conditions, and the estimation of…

Image and Video Processing · Electrical Eng. & Systems 2025-11-20 Jongyeon Yoon , Elyssa M. McMaster , Michael E. Kim , Gaurav Rudravaram , Kurt G. Schilling , Bennett A. Landman , Daniel Moyer

Diffusion functional MRI (dfMRI) is a promising technique to map functional activations by acquiring diffusion-weighed spin-echo images. In previous studies, dfMRI showed higher spatial accuracy at activation mapping compared to classic…

Medical Physics · Physics 2019-08-15 Alberto De Luca , Lara Schlaffke , Jeroen CW Siero , Martijn Froeling , Alexander Leemans

Diffraction tomography is a widely used inverse scattering technique for quantitative imaging of weakly scattering media. In its conventional formulation, diffraction tomography assumes monochromatic plane wave illumination. This…

Numerical Analysis · Mathematics 2026-03-11 Peter Elbau , Noemi Naujoks , Otmar Scherzer

Anisotropic Diffusion is widely used for noise reduction with simultaneous preservation of vascular structures in maximum intensity projected (MIP) angiograms. However, extension to minimum intensity projected (mIP) venograms in…

Computer Vision and Pattern Recognition · Computer Science 2015-01-15 P. K. Akshara , J. S. Paul