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In MRI, motion artefacts are among the most common types of artefacts. They can degrade images and render them unusable for accurate diagnosis. Traditional methods, such as prospective or retrospective motion correction, have been proposed…

Image and Video Processing · Electrical Eng. & Systems 2020-12-01 Soumick Chatterjee , Alessandro Sciarra , Max Dünnwald , Steffen Oeltze-Jafra , Andreas Nürnberger , Oliver Speck

Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis or mischaracterization in population-level imaging studies. Current retrospective rigid intra-slice motion correction techniques jointly optimize estimates of the…

Image and Video Processing · Electrical Eng. & Systems 2023-11-17 Nalini M. Singh , Neel Dey , Malte Hoffmann , Bruce Fischl , Elfar Adalsteinsson , Robert Frost , Adrian V. Dalca , Polina Golland

Segmenting anatomical structures in medical images has been successfully addressed with deep learning methods for a range of applications. However, this success is heavily dependent on the quality of the image that is being segmented. A…

Image and Video Processing · Electrical Eng. & Systems 2020-07-06 Ilkay Oksuz , James R. Clough , Bram Ruijsink , Esther Puyol Anton , Aurelien Bustin , Gastao Cruz , Claudia Prieto , Andrew P. King , Julia A. Schnabel

In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corruption of k-space lines, which can result in artefacts in the reconstructed images. In this paper, we propose a method to automatically detect and correct motion-related…

Image and Video Processing · Electrical Eng. & Systems 2019-06-14 lkay Oksuz , James Clough , Bram Ruijsink , Esther Puyol-Anton , Aurelien Bustin , Gastao Cruz , Claudia Prieto , Daniel Rueckert , Andrew P. King , Julia A. Schnabel

Motion artifacts in Magnetic Resonance Imaging (MRI) arise due to relatively long acquisition times and can compromise the clinical utility of acquired images. Traditional motion correction methods often fail to address severe motion,…

Image and Video Processing · Electrical Eng. & Systems 2024-07-04 Ziad Al-Haj Hemidi , Christian Weihsbach , Mattias P. Heinrich

Motion artifacts in Magnetic Resonance Imaging (MRI) are one of the frequently occurring artifacts due to patient movements during scanning. Motion is estimated to be present in approximately 30% of clinical MRI scans; however, motion has…

Image and Video Processing · Electrical Eng. & Systems 2024-05-29 Zhifeng Chen , Kamlesh Pawar , Kh Tohidul Islam , Himashi Peiris , Gary Egan , Zhaolin Chen

Magnetic Resonance Imaging (MRI) is a powerful medical imaging modality, but unfortunately suffers from long scan times which, aside from increasing operational costs, can lead to image artifacts due to patient motion. Motion during the…

Image and Video Processing · Electrical Eng. & Systems 2023-10-02 Brett Levac , Sidharth Kumar , Ajil Jalal , Jonathan I. Tamir

Abdominal magnetic resonance imaging (MRI) provides a straightforward way of characterizing tissue and locating lesions of patients as in standard diagnosis. However, abdominal MRI often suffers from respiratory motion artifacts, which…

Image and Video Processing · Electrical Eng. & Systems 2019-06-25 Wenhao Jiang , Zhiyu Liu , Kit-Hang Lee , Shihui Chen , Yui-Lun Ng , Qi Dou , Hing-Chiu Chang , Ka-Wai Kwok

Motion artifacts present in magnetic resonance imaging (MRI) can seriously interfere with clinical diagnosis. Removing motion artifacts is a straightforward solution and has been extensively studied. However, paired data are still heavily…

Image and Video Processing · Electrical Eng. & Systems 2024-12-12 Jiahua Xu , Dawei Zhou , Lei Hu , Jianfeng Guo , Feng Yang , Zaiyi Liu , Nannan Wang , Xinbo Gao

Motion represents one of the major challenges in magnetic resonance imaging (MRI). Since the MR signal is acquired in frequency space, any motion of the imaged object leads to complex artefacts in the reconstructed image in addition to…

Image and Video Processing · Electrical Eng. & Systems 2023-10-24 Veronika Spieker , Hannah Eichhorn , Kerstin Hammernik , Daniel Rueckert , Christine Preibisch , Dimitrios C. Karampinos , Julia A. Schnabel

Cine cardiac magnetic resonance imaging (MRI) is widely used for diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As compared to computed tomography (CT), MRI, however, requires a…

Image and Video Processing · Electrical Eng. & Systems 2020-06-24 Qing Lyu , Hongming Shan , Yibin Xie , Debiao Li , Ge Wang

Purpose To develop and evaluate a deep learning-based method (MC-Net) to suppress motion artifacts in brain magnetic resonance imaging (MRI). Methods MC-Net was derived from a UNet combined with a two-stage multi-loss function. T1-weighted…

Image and Video Processing · Electrical Eng. & Systems 2022-10-26 Lei Zhang , Xiaoke Wang , Michael Rawson , Radu Balan , Edward H. Herskovits , Elias Melhem , Linda Chang , Ze Wang , Thomas Ernst

Magnetic Resonance Imaging (MRI) is highly susceptible to motion artifacts due to the extended acquisition times required for k-space sampling. These artifacts can compromise diagnostic utility, particularly for dynamic imaging. We propose…

Image and Video Processing · Electrical Eng. & Systems 2025-07-04 Frederic Wang , Jonathan I. Tamir

Motion artifacts remain a significant challenge in Magnetic Resonance Imaging (MRI), compromising diagnostic quality and potentially leading to misdiagnosis or repeated scans. Existing deep learning approaches for motion artifact correction…

Image and Video Processing · Electrical Eng. & Systems 2025-11-24 Paolo Angella , Luca Balbi , Fabrizio Ferrando , Paolo Traverso , Rosario Varriale , Vito Paolo Pastore , Matteo Santacesaria

MRI, a widespread non-invasive medical imaging modality, is highly sensitive to patient motion. Despite many attempts over the years, motion correction remains a difficult problem and there is no general method applicable to all situations.…

Image and Video Processing · Electrical Eng. & Systems 2024-11-05 Oscar Dabrowski , Jean-Luc Falcone , Antoine Klauser , Julien Songeon , Michel Kocher , Bastien Chopard , François Lazeyras , Sébastien Courvoisier

Purpose: The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper is to develop a standalone novel technique to suppress motion artefacts from MR images using a data-driven deep learning approach.…

Image and Video Processing · Electrical Eng. & Systems 2020-10-08 Kamlesh Pawar , Zhaolin Chen , N. Jon Shah , Gary F. Egan

Motion artifacts are a common occurrence in the Magnetic Resonance Imaging (MRI) exam. Motion during acquisition has a profound impact on workflow efficiency, often requiring a repeat of sequences. Furthermore, motion artifacts may escape…

Image and Video Processing · Electrical Eng. & Systems 2021-03-16 Mohammad Reza Mohebbian , Ekta Walia , Khan A. Wahid

The presence of motion artifacts in magnetic resonance imaging (MRI) scans poses a significant challenge, where even minor patient movements can lead to artifacts that may compromise the scan's utility.This paper introduces MAsked MOtion…

Image and Video Processing · Electrical Eng. & Systems 2024-11-05 Lennart Alexander Van der Goten , Jingyu Guo , Kevin Smith

Cardiovascular Magnetic Resonance (CMR) plays an important role in the diagnoses and treatment of cardiovascular diseases while motion artifacts which are formed during the scanning process of CMR seriously affects doctors to find the exact…

Computer Vision and Pattern Recognition · Computer Science 2019-03-01 Yunxuan Zhang , Weiliang Zhang , Qinyan Zhang , Jijiang Yang , Xiuyu Chen , Shihua Zhao

Magnetic Resonance Imaging (MRI) is a widely used medical imaging modality boasting great soft tissue contrast without ionizing radiation, but unfortunately suffers from long acquisition times. Long scan times can lead to motion artifacts,…

Signal Processing · Electrical Eng. & Systems 2022-07-05 Brett Levac , Sidharth Kumar , Sofia Kardonik , Jonathan I. Tamir
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