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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

Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography. However, traditional methods face several limitations: they require extensive amounts of data,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Zhenyu Bu , Yang Liu , Jiayu Huo , Jingjing Peng , Kaini Wang , Guangquan Zhou , Rachel Sparks , Prokar Dasgupta , Alejandro Granados , Sebastien Ourselin

Echocardiography is a powerful prenatal examination tool for early diagnosis of fetal congenital heart diseases (CHDs). The four-chamber (FC) view is a crucial and easily accessible ultrasound (US) image among echocardiography images.…

Computer Vision and Pattern Recognition · Computer Science 2020-12-15 Sibo Qiao , Shanchen Pang , Gang Luo , Silin Pan , Xun Wang , Min Wang , Xue Zhai , Taotao Chen

As an important scan plane, four chamber view is routinely performed in both second trimester perinatal screening and fetal echocardiographic examinations. The biometrics in this plane including cardio-thoracic ratio (CTR) and cardiac axis…

Image and Video Processing · Electrical Eng. & Systems 2021-09-28 Jiancong Chen , Yingying Zhang , Jingyi Wang , Xiaoxue Zhou , Yihua He , Tong Zhang

Continuous monitoring of fetal and maternal vital signs, particularly during labor, can be critical for the child and mother's health. We present a novel wearable electronic system that measures, in real-time, maternal heart rate using…

Medical Physics · Physics 2023-07-03 Anushka Tiwari

Objective: To develop and interpret a supervised variational autoencoder (VAE) model for classifying cardiotocography (CTG) signals based on pregnancy outcomes, addressing interpretability limits of current deep learning approaches.…

Machine Learning · Computer Science 2025-09-09 John Tolladay , Beth Albert , Gabriel Davis Jones

Automatically identifying the structural substrates underlying cardiac abnormalities can potentially provide real-time guidance for interventional procedures. With the knowledge of cardiac tissue substrates, the treatment of complex…

Image and Video Processing · Electrical Eng. & Systems 2022-06-10 Ziyi Huang , Yu Gan , Theresa Lye , Yanchen Liu , Haofeng Zhang , Andrew Laine , Elsa Angelini , Christine Hendon

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

Prenatal screening with ultrasound can lower neonatal mortality significantly for selected cardiac abnormalities. However, the need for human expertise, coupled with the high volume of screening cases, limits the practically achievable…

Image and Video Processing · Electrical Eng. & Systems 2020-08-19 Jeremy Tan , Anselm Au , Qingjie Meng , Sandy FinesilverSmith , John Simpson , Daniel Rueckert , Reza Razavi , Thomas Day , David Lloyd , Bernhard Kainz

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

Remote patient monitoring based on wearable single-lead electrocardiogram (ECG) devices has significant potential for enabling the early detection of heart disease, especially in combination with artificial intelligence (AI) approaches for…

Signal Processing · Electrical Eng. & Systems 2024-04-30 Aruna Mohan , Danne Elbers , Or Zilbershot , Fatemeh Afghah , David Vorchheimer

The HeartBert model is introduced with three primary objectives: reducing the need for labeled data, minimizing computational resources, and simultaneously improving performance in machine learning systems that analyze Electrocardiogram…

Signal Processing · Electrical Eng. & Systems 2026-04-29 Saedeh Tahery , Fatemeh Hamid Akhlaghi , Termeh Amirsoleimani

Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning and deep learning, multiple approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Paula Ruiz-Barroso , Francisco M. Castro , José Miranda , Denisa-Andreea Constantinescu , David Atienza , Nicolás Guil

Cardiotocography (CTG) is a key element when it comes to monitoring fetal well-being. Obstetricians use it to observe the fetal heart rate (FHR) and the uterine contraction (UC). The goal is to determine how the fetus reacts to the…

Signal Processing · Electrical Eng. & Systems 2022-10-03 Julien Bertieaux , Mohammadhadi Shateri , Fabrice Labeau , Thierry Dutoit

Non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of the fetal heart. Decomposing the FECG signal from maternal ECG (MECG) is a blind source separation problem, which is hard due to the low amplitude of…

Signal Processing · Electrical Eng. & Systems 2021-02-11 Mohammad Reza Mohebbian , Seyed Shahim Vedaei , Khan A. Wahid , Anh Dinh , Hamid Reza Marateb , Kouhyar Tavakolian

Fetal heart motion is an important diagnostic indicator for structural detection and functional assessment of congenital heart disease. We propose an approach towards integrating deep convolutional and recurrent architectures that utilize…

Computer Vision and Pattern Recognition · Computer Science 2018-12-21 Arijit Patra , J. A. Noble

Monitoring the electrical pulse of fetal heart through a non-invasive fetal electrocardiogram (fECG) can easily detect abnormalities in the developing heart to significantly reduce the infant mortality rate and post-natal complications. Due…

Echocardiography is crucial for cardiovascular disease detection but relies heavily on experienced sonographers. Echocardiography probe guidance systems, which provide real-time movement instructions for acquiring standard plane images,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Yang Yue , Yulin Wang , Haojun Jiang , Pan Liu , Shiji Song , Gao Huang

The analysis of electrical impulse phenomena in cardiac muscle tissue is important for the diagnosis of heart rhythm disorders and other cardiac pathophysiology. Cardiac mapping techniques acquire local temporal measurements and combine…

Medical Physics · Physics 2022-03-21 Jan Lebert , Namita Ravi , Flavio Fenton , Jan Christoph

Congenital heart disease remains the most common congenital anomaly and a leading cause of neonatal morbidity and mortality. Although first-trimester fetal echocardiography offers an opportunity for earlier detection, automated analysis at…

Image and Video Processing · Electrical Eng. & Systems 2026-01-01 Youssef Megahed , Aylin Erman , Robin Ducharme , Mark C. Walker , Steven Hawken , Adrian D. C. Chan
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