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Related papers: Mesh-based 3D Motion Tracking in Cardiac MRI using…

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3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardiovascular diseases. Current state-of-the art methods focus on estimating dense…

Image and Video Processing · Electrical Eng. & Systems 2023-09-26 Qingjie Meng , Wenjia Bai , Declan P O'Regan , and Daniel Rueckert

Large prospective epidemiological studies acquire cardiovascular magnetic resonance (CMR) images for pre-symptomatic populations and follow these over time. To support this approach, fully automatic large-scale 3D analysis is essential. In…

Image and Video Processing · Electrical Eng. & Systems 2019-07-04 Rahman Attar , Marco Pereanez , Christopher Bowles , Stefan K. Piechnik , Stefan Neubauer , Steffen E. Petersen , Alejandro F. Frangi

Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR) imaging enables the assessment of regional myocardial function and is important for understanding and analyzing cardiovascular disease. However, 3D cardiac…

Image and Video Processing · Electrical Eng. & Systems 2022-08-02 Qingjie Meng , Chen Qin , Wenjia Bai , Tianrui Liu , Antonio de Marvao , Declan P O'Regan , Daniel Rueckert

Automated construction of surface geometries of cardiac structures from volumetric medical images is important for a number of clinical applications. While deep-learning-based approaches have demonstrated promising reconstruction precision,…

Image and Video Processing · Electrical Eng. & Systems 2021-09-15 Fanwei Kong , Nathan Wilson , Shawn C. Shadden

Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise over time. Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Sven Koehler , Tarique Hussain , Hamza Hussain , Daniel Young , Samir Sarikouch , Thomas Pickhardt , Gerald Greil , Sandy Engelhardt

Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often struggle to capture heart motion accurately because they…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Reza Akbari Movahed , Abuzar Rezaee , Arezoo Zakeri , Colin Berry , Edmond S. L. Ho , Ali Gooya

Patient-specific cardiac modeling combines geometries of the heart derived from medical images and biophysical simulations to predict various aspects of cardiac function. However, generating simulation-suitable models of the heart from…

Image and Video Processing · Electrical Eng. & Systems 2023-11-09 Fanwei Kong , Shawn Shadden

Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel deep learning method for joint estimation of motion and…

Computer Vision and Pattern Recognition · Computer Science 2018-06-12 Chen Qin , Wenjia Bai , Jo Schlemper , Steffen E. Petersen , Stefan K. Piechnik , Stefan Neubauer , Daniel Rueckert

Accurate analysis of cardiac motion is crucial for evaluating cardiac function. While dynamic cardiac magnetic resonance imaging (CMR) can capture detailed tissue motion throughout the cardiac cycle, the fine-grained 4D cardiac motion…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xueming Fu , Pei Wu , Yingtai Li , Xin Luo , Zihang Jiang , Junhao Mei , Jian Lu , Gao-Jun Teng , S. Kevin Zhou

Image-based computer simulation of cardiac function can be used to probe the mechanisms of (patho)physiology, and guide diagnosis and personalized treatment of cardiac diseases. This paradigm requires constructing simulation-ready meshes of…

Image and Video Processing · Electrical Eng. & Systems 2021-07-23 Fanwei Kong , Shawn C. Shadden

Cardiac Magnetic Resonance (CMR) imaging serves as the gold-standard for evaluating cardiac morphology and function. Typically, a multi-view CMR stack, covering short-axis (SA) and 2/3/4-chamber long-axis (LA) views, is acquired for a…

Image and Video Processing · Electrical Eng. & Systems 2025-07-03 Yundi Zhang , Chen Chen , Suprosanna Shit , Sophie Starck , Daniel Rueckert , Jiazhen Pan

To facilitate diagnosis on cardiac ultrasound (US), clinical practice has established several standard views of the heart, which serve as reference points for diagnostic measurements and define viewports from which images are acquired.…

Image and Video Processing · Electrical Eng. & Systems 2024-03-04 Sarina Thomas , Cristiana Tiago , Børge Solli Andreassen , Svein Arne Aase , Jurica Šprem , Erik Steen , Anne Solberg , Guy Ben-Yosef

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

Automated segmentation of Cardiac Magnetic Resonance (CMR) plays a pivotal role in efficiently assessing cardiac function, offering rapid clinical evaluations that benefit both healthcare practitioners and patients. While recent research…

Image and Video Processing · Electrical Eng. & Systems 2024-06-14 Abdul Qayyum , Hao Xu , Brian P. Halliday , Cristobal Rodero , Christopher W. Lanyon , Richard D. Wilkinson , Steven Alexander Niederer

Mesh reconstruction of the cardiac anatomy from medical images is useful for shape and motion measurements and biophysics simulations to facilitate the assessment of cardiac function and health. However, 3D medical images are often acquired…

Image and Video Processing · Electrical Eng. & Systems 2024-10-22 Yihao Luo , Dario Sesia , Fanwen Wang , Yinzhe Wu , Wenhao Ding , Jiahao Huang , Fadong Shi , Anoop Shah , Amit Kaural , Jamil Mayet , Guang Yang , ChoonHwai Yap

Myocardial motion tracking stands as an essential clinical tool in the prevention and detection of cardiovascular diseases (CVDs), the foremost cause of death globally. However, current techniques suffer from incomplete and inaccurate…

Image and Video Processing · Electrical Eng. & Systems 2024-06-28 Chengkang Shen , Hao Zhu , You Zhou , Yu Liu , Si Yi , Lili Dong , Weipeng Zhao , David J. Brady , Xun Cao , Zhan Ma , Yi Lin

Cardiac motion estimation plays a key role in MRI cardiac feature tracking and function assessment such as myocardium strain. In this paper, we propose Motion Pyramid Networks, a novel deep learning-based approach for accurate and efficient…

Image and Video Processing · Electrical Eng. & Systems 2020-09-17 Hanchao Yu , Xiao Chen , Humphrey Shi , Terrence Chen , Thomas S. Huang , Shanhui Sun

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

Myocardial motion tracking is important for assessing cardiac function and diagnosing cardiovascular diseases, for which cine cardiac magnetic resonance (CMR) has been established as the gold standard imaging modality. Many existing methods…

Image and Video Processing · Electrical Eng. & Systems 2025-07-24 Jiahui Yin , Xinxing Cheng , Jinming Duan , Yan Pang , Declan O'Regan , Hadrien Reynaud , Qingjie Meng

Cardiovascular magnetic resonance (CMR) is the gold standard for assessing cardiac function, but individual cardiac cycles complicate automatic temporal comparison or sub-phase analysis. Accurate cardiac keyframe detection can eliminate…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Sven Koehler , Sarah Kaye Mueller , Jonathan Kiekenap , Gerald Greil , Tarique Hussain , Samir Sarikouch , Florian André , Norbert Frey , Sandy Engelhardt
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