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The European Heart Journal-Cardiovascular Imaging was launched in 2012 and has during these years become one of the leading multimodality cardiovascular imaging journal. The journal is now established as one of the top cardiovascular journals and is the most important cardiovascular imaging journal in Europe. The most important studies published in our Journal from 2020 will be highlighted in two reports. Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease. While Part I of the review has focused on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging.
The European Heart Journal-Cardiovascular Imaging was introduced in 2012 and has during these 10 years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as Number 19 among all cardiovascular journals. It has an impressive impact factor of 9.130 and our journal is well established as one of the top cardiovascular journals. The most important studies published in our Journal in 2021 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
European Heart Journal - Cardiovascular Imaging was launched in 2012 as a multimodality cardiovascular imaging journal. It has gained an impressive impact factor during its first 5 years and is now established as one of the top cardiovascular journals and has become the most important cardiovascular imaging journal in Europe. The most important studies from 2018 will be highlighted in two reports. Part I of the review has focused on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on cardiomyopathies, congenital heart diseases, valvular heart diseases, and heart failure.
The European Heart Journal - Cardiovascular Imaging was launched in 2012 and has during these 9 years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as number 20 among all cardiovascular journals. Our journal is well established as one of the top cardiovascular journals and is the most important cardiovascular imaging journal in Europe. The most important studies published in our Journal in 2020 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
Cardiovascular diseases (CVDs) encompass a group of disorders affecting the heart and blood vessels, including conditions such as coronary artery disease, heart failure, stroke, and hypertension. In cardiovascular diseases, heart failure is one of the main causes of death and also long-term suffering in patients worldwide. Prediction is one of the risk factors that is highly valuable for treatment and intervention to minimize heart failure. In this work, an attention learning-based heart failure prediction approach is proposed on EHR(electronic health record) cardiovascular data such as ejection fraction and serum creatinine. Moreover, different optimizers with various learning rate approaches are applied to fine-tune the proposed approach. Serum creatinine and ejection fraction are the two most important features to predict the patient's heart failure. The computational result shows that the RMSProp optimizer with 0.001 learning rate has a better prediction based on serum creatinine. On the other hand, the combination of SGD optimizer with 0.01 learning rate exhibits optimum performance based on ejection fraction features. Overall, the proposed attention learning-based approach pe
The European Heart Journal - Cardiovascular Imaging has become one of the leading multimodality cardiovascular imaging journal, since it was launched in 2012. The impact factor is an impressive 8.366 and it is now established as one of the top 10 cardiovascular journals. The journal is the most important cardiovascular imaging journal in Europe. The most important studies from 2018 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
The European Heart Journal-Cardiovascular Imaging was launched in 2012 and has during these years become one of the leading multimodality cardiovascular imaging journals. The journal is now established as one of the top cardiovascular journals and is the most important cardiovascular imaging journal in Europe. The most important studies published in our Journal in 2019 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
The European Research and Development for Space based High Contrast Imaging II Workshop, held at MPIA in May 2025, advanced Europe strategic coordination in support of future exoplanet imaging missions such as the Habitable Worlds Observatory and the Large Interferometer for Exoplanets mission. Building on the first 2024 workshop, this meeting defined concrete priorities across eight technical areas, including wavefront sensing, coronagraphs, post processing, nulling interferometry, deformable mirrors, detectors, and telescope design. Discussions emphasized Europe strengths in adaptive optics, ground-based facilities, and interferometry, while identifying key gaps, particularly the need for a dedicated European vacuum testbed for high contrast imaging. The community highlighted near infrared or UV coronagraphy as a promising domain for European leadership and called for joint development of advanced data reduction algorithms, detectors, and cross-mission coordination with HWO and LIFE. The workshop outcomes establish a collaborative roadmap to strengthen Europe technological readiness, foster agency partnerships, and ensure its continued leadership in the next generation of space-b
The multimodality cardiovascular imaging journal, European Heart Journal-Cardiovascular Imaging, was launched in 2012. It has gained an impressive impact factor of 5.99 during its 5 first years and is now established as the most important cardiovascular imaging journal in Europe. The most important studies from the journal's forth and fifth years will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
The European Heart Journal - Cardiovascular Imaging was launched in 2012. It has gained an impressive impact factor of 8.336 during its first 6 years and is now established as one of the top 10 cardiovascular journals in the world and the most important cardiovascular imaging journal in Europe. The most important studies published in the journal in 2017 will be highlighted in two reports. Part I will focus on studies about myocardial function, coronary artery disease and myocardial ischaemia, and emerging techniques and applications in cardiovascular imaging, whereas Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.
The oscillations of the human heart rate are inherently complex and non-linear -- they are best described by mathematical chaos, and they present a challenge when applied to the practical domain of cardiovascular health monitoring in everyday life. In this work, we study the non-linear chaotic behavior of heart rate through mutual information and introduce a novel approach for enhancing heart rate estimation in real-life conditions. Our proposed approach not only explains and handles the non-linear temporal complexity from a mathematical perspective but also improves the deep learning solutions when combined with them. We validate our proposed method on four established datasets from real-life scenarios and compare its performance with existing algorithms thoroughly with extensive ablation experiments. Our results demonstrate a substantial improvement, up to 40\%, of the proposed approach in estimating heart rate compared to traditional methods and existing machine-learning techniques while reducing the reliance on multiple sensing modalities and eliminating the need for post-processing steps.
The multi-modality cardiovascular imaging journal, European Heart Journal-Cardiovascular Imaging, was created in 2012. It has gained an impressive impact factor of 5.99 during its first 5 years and is now the most important imaging journal in Europe. The most important studies from the journal's fourth and fifth years will be highlighted in two reports. Part I of the review will focus on studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging and Part II will focus on valvular heart diseases, heart failure, cardiomyopathies, and congenital heart diseases.
The new multimodality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was created in 2012. It has already gained an impressive impact factor of 3.669 during its first 2 years. In two articles, we will summarize the most important studies from the journal's third year. Part I of the review will focus on studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging, and Part II will focus on valvular heart diseases, heart failure, cardiomyopathies, and congenital heart diseases.
The new multimodality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was created in 2012. Here, we summarize the most important studies from the journal's second year in two articles. Part I of the review will focus on studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging, and Part II will focus on valvular heart diseases, heart failure, cardiomyopathies, and congenital heart diseases.
The European Heart Journal-Cardiovascular Imaging, created in 2012, has become a reference for publishing multimodality cardiovascular imaging scientific and review papers. The impressive 2014 impact factor of 4.105 confirms the important position of our journal. In this part, we summarize the most important studies from the journal's third year, with specific emphasis on cardiomyopathies, congenital heart diseases, valvular heart diseases, and heart failure.
How do you use imaging to analyse the development of the heart, which not only changes shape but also undergoes constant, high-speed, quasi-periodic changes? We have integrated ideas from prospective and retrospective optical gating to capture long-term, phase-locked developmental time-lapse videos. In this paper we demonstrate the success of this approach over a key developmental time period: heart looping, where large changes in heart shape prevent previous prospective gating approaches from capturing phase-locked videos. We use the comparison with other approaches to in vivo heart imaging to highlight the importance of collecting the most appropriate data for the biological question.
A unique and highly versatile technique, stress echocardiography (SE) is increasingly recognized for its utility in the evaluation of non-ischaemic heart disease. SE allows for simultaneous assessment of myocardial function and haemodynamics under physiological or pharmacological conditions. Due to its diagnostic and prognostic value, SE has become widely implemented to assess various conditions other than ischaemic heart disease. It has thus become essential to establish guidance for its applications and performance in the area of non-ischaemic heart disease. This paper summarizes these recommendations.
Congenital heart disease (CHD) screening from fetal echocardiography requires accurate analysis of multiple standard cardiac views, yet developing reliable artificial intelligence models remains challenging due to limited annotations and variable image quality. In this work, we propose FM-DACL, a semi-supervised Dual Agreement Consistency Learning framework for the FETUS 2026 challenge on fetal heart ultrasound segmentation and diagnosis. The method combines a pretrained ultrasound foundation model (EchoCare) with a convolutional network through heterogeneous co-training and an exponential moving average teacher to better exploit unlabeled data. Experiments on the multi-center challenge dataset show that FM-DACL achieves a Dice score of 59.66 and NSD of 42.82 using heterogeneous backbones, demonstrating the feasibility of the proposed semi-supervised framework. These results suggest that FM-DACL provides a flexible approach for leveraging heterogeneous models in low-annotation fetal cardiac ultrasound analysis. The code is available on https://github.com/13204942/FM-DACL.
As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality exposures in large imaging surveys, with a focus on the DECam Legacy Survey (DECaLS) in regions of low extinction (i.e., $E(B-V)<0.04$). Our semi-supervised pipeline integrates a vision transformer (ViT), trained via self-supervised learning (SSL), with a k-Nearest Neighbor (kNN) classifier. We train and validate our pipeline using a small set of labeled exposures observed by surveys with the Dark Energy Camera (DECam). A clustering-space analysis of where our pipeline places images labeled in ``good'' and ``bad'' categories suggests that our approach can efficiently and accurately determine the quality of exposures. Applied to new imaging being reduced for DECaLS Data Release 11, our pipeline identifies 780 problematic exposures, which we subsequently verify through visual inspection. Being highly efficient and adaptable, our method offers a scalable solution for quality control in other large imaging surveys.
We present a novel computerized fetal heart rate intrapartum algorithm for early and individualized prediction of fetal cardiovascular decompensation, a key event in the causal chain leading to brain injury. This real-time machine learning algorithm performs well on noisy fetal heart rate data and requires ~2 hours to train on the individual fetal heart rate tracings in the first stage of labor; once trained, the algorithm predicts the event of fetal cardiovascular decompensation with 92% sensitivity. We show that the algorithm's performance suffers reducing sensitivity to 67% when the fetal heart rate is acquired at the sampling rate of 4 Hz used in ultrasound cardiotocographic monitors compared to the electrocardiogram(ECG)-derived signals as can be acquired from maternal abdominal ECG.