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Related papers: Physics-Aware Motion Simulation for T2*-Weighted B…

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Magnetic Resonance Imaging (MRI) provides detailed tissue information, but its clinical application is limited by long acquisition time, high cost, and restricted resolution. Image translation has recently gained attention as a strategy to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Xihe Qiu , Yang Dai , Xiaoyu Tan , Sijia Li , Fenghao Sun , Lu Gan , Liang Liu

Studies of the human brain during natural activities, such as locomotion, would benefit from the ability to image deep brain structures during these activities. While Positron Emission Tomography (PET) can image these structures, the bulk…

Robotics · Computer Science 2023-11-30 Junxiang Wang , Iulian I. Iordachita , Peter Kazanzides

Low-field magnetic resonance imaging (MRI) offers a cost-effective alternative for medical imaging in resource-limited settings. However, its widespread adoption is hindered by two key challenges: prolonged scan times and reduced image…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Daniel Tweneboah Anyimadu , Mohammed Abdalla , Mohammed M. Abdelsamea , Ahmed Karam Eldaly

Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional myocardium deformation and cardiac strain estimation. However, this technique has not been widely used in clinical diagnosis, as a result of the difficulty…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Meng Ye , Mikael Kanski , Dong Yang , Qi Chang , Zhennan Yan , Qiaoying Huang , Leon Axel , Dimitris Metaxas

T2 weighted imaging of the spine is commonly performed using fast spin echo (FSE/TSE) based sequences, resulting in long scan times and vulnerability to motion artifacts. While single shot fast spin echo sequences have been attempted, their…

This work introduces a novel approach to fMRI-based visual image reconstruction using a subject-agnostic common representation space. We show that the brain signals of the subjects can be aligned in this common space during training to form…

Image and Video Processing · Electrical Eng. & Systems 2025-10-10 Christos Zangos , Danish Ebadulla , Thomas Christopher Sprague , Ambuj Singh

Purpose: To assess whether breast lesion segmentation can be learned directly from acquired MRI k-space, and whether doing so improves robustness when data are accelerated or noisy. Materials and Methods: This retrospective study used…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Lukas T. Rotkopf , Marco Schlimbach , Julius C. Holzschuh , Heinz-Peter Schlemmer , Jens Kleesiek , Moritz Rempe

Magnetic Resonance Imaging generally requires long exposure times, while being sensitive to patient motion, resulting in artifacts in the acquired images, which may hinder their diagnostic relevance. Despite research efforts to decrease the…

Image and Video Processing · Electrical Eng. & Systems 2025-02-04 Paolo Angella , Vito Paolo Pastore , Matteo Santacesaria

We describe an acquisition/processing procedure for image reconstruction in dynamic Magnetic Resonance Imaging (MRI). The approach requires sliding window to record a set of trajectories in the k-space, standard regularization to…

Computational Engineering, Finance, and Science · Computer Science 2014-02-12 Cristian Toraci , Gabriele Zaccaria , Stefano Ceriani , David Wilson , Marco Fato , Michele Piana

Magnetic Resonance Imaging (MRI) stands as a powerful modality in clinical diagnosis. However, it is known that MRI faces challenges such as long acquisition time and vulnerability to motion-induced artifacts. Despite the success of many…

Image and Video Processing · Electrical Eng. & Systems 2023-10-17 Lixuan Chen , Xuanyu Tian , Jiangjie Wu , Ruimin Feng , Guoyan Lao , Yuyao Zhang , Hongjiang Wei

Functional magnetic resonance imaging (fMRI) is now a well-established technique for studying the brain. However, in many situations, such as when data are acquired in a resting state, it is difficult to know whether the data are truly…

Applications · Statistics 2013-01-15 John A. D. Aston , Claudia Kirch

Despite the superior diagnostic capability of Magnetic Resonance Imaging (MRI), its use as a Point-of-Care (PoC) device remains limited by high cost and complexity. To enable such a future by reducing the magnetic field strength, one key…

Image and Video Processing · Electrical Eng. & Systems 2026-02-16 Yuning Du , Jingshuai Liu , Rohan Dharmakumar , Sotirios A. Tsaftaris

Due to the visual ambiguity, purely kinematic formulations on monocular human motion capture are often physically incorrect, biomechanically implausible, and can not reconstruct accurate interactions. In this work, we focus on exploiting…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Buzhen Huang , Liang Pan , Yuan Yang , Jingyi Ju , Yangang Wang

With the wide adoption of functional magnetic resonance imaging (fMRI) by cognitive neuroscience researchers, large volumes of brain imaging data have been accumulated in recent years. Aggregating these data to derive scientific insights…

Applications · Statistics 2020-06-01 Ming Bo Cai , Michael Shvartsman , Anqi Wu , Hejia Zhang , Xia Zhu

Active soft bodies can affect their shape through an internal actuation mechanism that induces a deformation. Similar to recent work, this paper utilizes a differentiable, quasi-static, and physics-based simulation layer to optimize for…

Computer Vision and Pattern Recognition · Computer Science 2024-01-29 Lingchen Yang , Byungsoo Kim , Gaspard Zoss , Baran Gözcü , Markus Gross , Barbara Solenthaler

We present a new trainable system for physically plausible markerless 3D human motion capture, which achieves state-of-the-art results in a broad range of challenging scenarios. Unlike most neural methods for human motion capture, our…

Computer Vision and Pattern Recognition · Computer Science 2021-05-04 Soshi Shimada , Vladislav Golyanik , Weipeng Xu , Patrick Pérez , Christian Theobalt

We address the problem of active mapping with a continually-learned neural scene representation, namely Active Neural Mapping. The key lies in actively finding the target space to be explored with efficient agent movement, thus minimizing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Zike Yan , Haoxiang Yang , Hongbin Zha

Purpose: Advancements in MRI Tissue Phase Velocity Mapping (TPM) allow for the acquisition of higher quality velocity cardiac images providing better assessment of regional myocardial deformation for accurate disease diagnosis,…

Medical Physics · Physics 2018-08-21 Christina Koutsoumpa , Jennifer Keegan , David Firmin , Guang-Zhong Yang , Duncan Gillies

Quantitative Magnetic Resonance Imaging (qMRI) provides researchers insight into pathological and physiological alterations of living tissue, with the help of which researchers hope to predict (local) therapeutic efficacy early and…

Applications · Statistics 2008-07-30 Xiaoxi Zhang , Timothy D. Johnson , Roderick J. A. Little , Yue Cao

Background: A noninvasive and sensitive imaging tool is needed to assess the fast-evolving baby brain. However, using MRI to study non-sedated babies faces roadblocks, including high scan failure rates due to subjects motion and the lack of…