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Objective: To test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Background: Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive…

Image and Video Processing · Electrical Eng. & Systems 2019-07-04 Ryan J. Cunningham , Ian D. Loram

Dynamic contrast-enhanced (DCE) MRI is essential for breast cancer diagnosis and treatment. However, its reliance on contrast agents introduces safety concerns, contraindications, increased cost, and workflow complexity. To this end, we…

Image and Video Processing · Electrical Eng. & Systems 2025-09-16 Sebastian Ibarra , Javier del Riego , Alessandro Catanese , Julian Cuba , Julian Cardona , Nataly Leon , Jonathan Infante , Karim Lekadir , Oliver Diaz , Richard Osuala

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial method for white matter (WM) parcellation to enable analysis of brains structural connectivity in health and disease. Current fiber clustering strategies primarily use…

Image and Video Processing · Electrical Eng. & Systems 2025-11-04 Bocheng Guo , Jin Wang , Yijie Li , Junyi Wang , Mingyu Gao , Puming Feng , Yuqian Chen , Jarrett Rushmore , Nikos Makris , Yogesh Rathi , Lauren J O'Donnell , Fan Zhang

Diffusion magnetic resonance imaging (dMRI) provides critical insights into the microstructural and connectional organization of the human brain. However, the availability of high-field, open-access datasets that include raw k-space data…

Image and Video Processing · Electrical Eng. & Systems 2024-12-10 Shanshan Wang , Shoujun Yu , Jian Cheng , Sen Jia , Changjun Tie , Jiayu Zhu , Haohao Peng , Yijing Dong , Jianzhong He , Fan Zhang , Yaowen Xing , Xiuqin Jia , Qi Yang , Qiyuan Tian , Hua Guo , Guobin Li , Hairong Zheng

A model-based reconstruction technique for accelerated T2 mapping with improved accuracy is proposed using undersampled Cartesian spin-echo MRI data. The technique employs an advanced signal model for T2 relaxation that accounts for…

Medical Physics · Physics 2015-03-03 Tilman J. Sumpf , Andreas Petrovic , Martin Uecker , Florian Knoll , Jens Frahm

Incoherent k-space undersampling and deep learning-based reconstruction methods have shown great success in accelerating MRI. However, the performance of most previous methods will degrade dramatically under high acceleration factors, e.g.,…

Image and Video Processing · Electrical Eng. & Systems 2026-01-21 Jin Liu , Qing Lin , Zhuang Xiong , Shanshan Shan , Chunyi Liu , Min Li , Feng Liu , G. Bruce Pike , Hongfu Sun , Yang Gao

Deep learning has emerged as a promising approach for learning the nonlinear mapping between diffusion-weighted MR images and tissue parameters, which enables automatic and deep understanding of the brain microstructures. However, the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Wenxin Fan , Jian Cheng , Qiyuan Tian , Ruoyou Wu , Juan Zou , Zan Chen , Shanshan Wang

Magnetic Resonance Imaging (MRI) is a crucial diagnostic tool, but high-resolution scans are often slow and expensive due to extensive data acquisition requirements. Traditional MRI reconstruction methods aim to expedite this process by…

Image and Video Processing · Electrical Eng. & Systems 2025-11-11 Emmanuelle Bourigault , Abdullah Hamdi , Amir Jamaludin

Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique used to characterize microstructural changes in the brain. DTI studies quantify the diffusion of water molecules in a voxel using an estimated 3x3 symmetric…

Methodology · Statistics 2021-03-30 Zhou Lan , Brian J. Reich , Dipankar Bandyopadhyay

Diffusion-weighted magnetic resonance imaging (DW-MRI) derived scalar maps are effective for assessing neurodegenerative diseases and microstructural properties of white matter in large number of brain conditions. However, DW-MRI inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Gabriel Girard , Manon Edde , Félix Dumais , Yoan David , Matthieu Dumont , Guillaume Theaud , Jean-Christophe Houde , Arnaud Boré , Maxime Descoteaux , Pierre-Marc Jodoin

Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and…

Medical Physics · Physics 2019-02-07 Jukka Hirvasniemi , Jaakko Niinimäki , Jérôme Thevenot , Simo Saarakkala

Magnetic resonance imaging (MRI) is a powerful medical imaging modality, but long acquisition times limit throughput, patient comfort, and clinical accessibility. Diffusion-based generative models serve as strong image priors for reducing…

Machine Learning · Computer Science 2026-02-13 Sriram Ravula , Brett Levac , Yamin Arefeen , Ajil Jalal , Alexandros G. Dimakis , Jonathan I. Tamir

Magnetic resonance imaging (MRI) enables non-invasive, high-resolution analysis of muscle structures. However, automated segmentation remains limited by high computational costs, reliance on large training datasets, and reduced accuracy in…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Mengyuan Liu , Jeongkyu Lee

Diffusion magnetic resonance imaging is an imaging technology designed to probe anatomical architectures of biological samples in an in vivo and non-invasive manner through measuring water diffusion. The contribution of this paper is…

Purpose: Investigation of the feasibility of the R2* mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio. Theory and Methods: The improvement of the performance of…

Medical Physics · Physics 2016-08-10 G. Siracusano , A. La Corte , C. Milazzo , G. P. Anastasi , G. Finocchio , M. Gaeta

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

The purpose of this work is to develop a deep learning-based method for knee menisci segmentation in 3D ultrashort echo time (UTE) cones magnetic resonance (MR) imaging, and to automatically determine MR relaxation times, namely the T1,…

Image and Video Processing · Electrical Eng. & Systems 2019-08-06 Michal Byra , Mei Wu , Xiaodong Zhang , Hyungseok Jang , Ya-Jun Ma , Eric Y Chang , Sameer Shah , Jiang Du

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning and monitoring of many neurological…

Image and Video Processing · Electrical Eng. & Systems 2024-04-29 Megan E. Farquhar , Qianqian Yang , Viktor Vegh

We present a new approach for representing and reconstructing multidimensional magnetic resonance imaging (MRI) data. Our method builds on a novel, learned feature-based image representation that disentangles different types of features,…

Image and Video Processing · Electrical Eng. & Systems 2026-01-01 Ruiyang Zhao , Fan Lam

Knee osteoarthritis (KOA) is a prevalent musculoskeletal disorder, often diagnosed using X-rays due to its cost-effectiveness. While Magnetic Resonance Imaging (MRI) provides superior soft tissue visualization and serves as a valuable…

Image and Video Processing · Electrical Eng. & Systems 2024-12-30 Zhe Wang , Yung Hsin Chen , Aladine Chetouani , Fabian Bauer , Yuhua Ru , Fang Chen , Liping Zhang , Rachid Jennane , Mohamed Jarraya