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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

Feature tracking Cardiac Magnetic Resonance (CMR) has recently emerged as an area of interest for quantification of regional cardiac function from balanced, steady state free precession (SSFP) cine sequences. However, currently available…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Davis M. Vigneault , Weidi Xie , David A. Bluemke , J. Alison Noble

The identification of cardiac phase is an essential step for analysis and diagnosis of cardiac function. Automatic methods, especially data-driven methods for cardiac phase detection, typically require extensive annotations, which is…

Image and Video Processing · Electrical Eng. & Systems 2025-11-17 Yingyu Yang , Qianye Yang , Kangning Cui , Can Peng , Elena D'Alberti , Netzahualcoyotl Hernandez-Cruz , Olga Patey , Aris T. Papageorghiou , J. Alison Noble

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 Velocity Mapping Cardiac MR (MVM-CMR) can be used to measure global and regional myocardial velocities with proved reproducibility. Accurate left ventricle delineation is a prerequisite for robust and reproducible myocardial…

Image and Video Processing · Electrical Eng. & Systems 2021-04-28 Mengmeng Kuang , Yinzhe Wu , Diego Alonso-Álvarez , David Firmin , Jennifer Keegan , Peter Gatehouse , Guang Yang

Quantification of cardiac motion with cine Cardiac Magnetic Resonance Imaging (CMRI) is an integral part of arrhythmogenic right ventricular cardiomyopathy (ARVC) diagnosis. Yet, the expert evaluation of motion abnormalities with CMRI is a…

Image and Video Processing · Electrical Eng. & Systems 2023-11-27 Laura Alvarez-Florez , Jörg Sander , Mimount Bourfiss , Fleur V. Y. Tjong , Birgitta K. Velthuis , Ivana Išgum

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

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

Motion scoring of cardiac myocardium is of paramount importance for early detection and diagnosis of various cardiac disease. It aims at identifying regional wall motions into one of the four types including normal, hypokinetic, akinetic,…

Computer Vision and Pattern Recognition · Computer Science 2018-06-15 Wufeng Xue , Gary Brahm , Stephanie Leung , Ogla Shmuilovich , Shuo Li

Cardiac Magnetic Resonance (CMR) is the most effective tool for the assessment and diagnosis of a heart condition, which malfunction is the world's leading cause of death. Software tools leveraging Artificial Intelligence already enhance…

Computer Vision and Pattern Recognition · Computer Science 2021-03-16 Adrianna Janik , Jonathan Dodd , Georgiana Ifrim , Kris Sankaran , Kathleen Curran

Accurate motion estimation in cardiac computed tomography (CT) imaging is critical for assessing cardiac function and surgical planning. Data-driven methods have become the standard approach for dense motion estimation, but they rely on…

Image and Video Processing · Electrical Eng. & Systems 2025-07-23 Shahar Zuler , Gal Lifshitz , Hadar Averbuch-Elor , Dan Raviv

Accurate segmentation of the heart is an important step towards evaluating cardiac function. In this paper, we present a fully automated framework for segmentation of the left (LV) and right (RV) ventricular cavities and the myocardium…

Computer Vision and Pattern Recognition · Computer Science 2017-10-11 Christian F. Baumgartner , Lisa M. Koch , Marc Pollefeys , Ender Konukoglu

Accurate 3D cardiac reconstruction from cine magnetic resonance imaging (cMRI) is crucial for improved cardiovascular disease diagnosis and understanding of the heart's motion. However, current cardiac MRI-based reconstruction technology…

Image and Video Processing · Electrical Eng. & Systems 2023-08-21 Xiaoxiao He , Chaowei Tan , Ligong Han , Bo Liu , Leon Axel , Kang Li , Dimitris N. Metaxas

This study proposes an end-to-end unsupervised diffeomorphic deformable registration framework based on moving mesh parameterization. Using this parameterization, a deformation field can be modeled with its transformation Jacobian…

Image and Video Processing · Electrical Eng. & Systems 2022-08-30 Ameneh Sheikhjafari , Deepa Krishnaswamy , Michelle Noga , Nilanjan Ray , Kumaradevan Punithakumar

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

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

While deep learning has achieved significant advances in accuracy for medical image segmentation, its benefits for deformable image registration have so far remained limited to reduced computation times. Previous work has either focused on…

Computer Vision and Pattern Recognition · Computer Science 2018-12-06 Alessa Hering , Sven Kuckertz , Stefan Heldmann , Mattias Heinrich

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

Patient-specific left ventricle (LV) myocardial models have the potential to be used in a variety of clinical scenarios for improved diagnosis and treatment plans. Cine cardiac magnetic resonance (MR) imaging provides high resolution images…

Image and Video Processing · Electrical Eng. & Systems 2021-04-01 Roshan Reddy Upendra , Brian Jamison Wentz , Richard Simon , Suzanne M. Shontz , Cristian A. Linte

Diffusion tensor cardiac magnetic resonance (DT-CMR) is a method capable of providing non-invasive measurements of myocardial microstructure. Image registration is essential to correct image shifts due to intra and inter breath-hold motion…

Image and Video Processing · Electrical Eng. & Systems 2024-05-17 Fanwen Wang , Pedro F. Ferreira , Yinzhe Wu , Camila Munoz , Ke Wen , Yaqing Luo , Jiahao Huang , Dudley J. Pennell , Andrew D. Scott , Sonia Nielles-Vallespin , Guang Yang