1.2k citations · 1.3k across the 10 of their papers we have counts for
11 papers
3D Cardiac Anatomy Generation Using Mesh Latent Diffusion Models
Jolanta Mozyrska, Marcel Beetz, Luke Melas-Kyriazi +3
Diffusion models have recently gained immense interest for their generative capabilities, specifically the high quality and diversity of the synthesized data. However, examples of…
An Automated Computational Pipeline for Generating Large-Scale Cohorts of Patient-Specific Ventricular Models in Electromechanical In Silico Trials
Ruben Doste, Julia Camps, Zhinuo Jenny Wang +8
In recent years, human in silico trials have gained significant traction as a powerful approach to evaluate the effects of drugs, clinical interventions, and medical devices. In si…
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
Chen Chen, Lei Li, Marcel Beetz +3
Heart failure (HF) poses a significant public health challenge, with a rising global mortality rate. Early detection and prevention of HF could significantly reduce its impact. We…
Anatomical basis of sex differences in the electrocardiogram identified by three-dimensional torso-heart imaging reconstruction pipeline
Hannah J. Smith, Blanca Rodriguez, Yuling Sang +4
The electrocardiogram (ECG) is used for diagnosis and risk stratification in myocardial infarction (MI). Women have a higher incidence of missed MI diagnosis and complications foll…
Multi-objective point cloud autoencoders for explainable myocardial infarction prediction
Marcel Beetz, Abhirup Banerjee, Vicente Grau
Myocardial infarction (MI) is one of the most common causes of death in the world. Image-based biomarkers commonly used in the clinic, such as ejection fraction, fail to capture mo…
Modeling 3D cardiac contraction and relaxation with point cloud deformation networks
Marcel Beetz, Abhirup Banerjee, Vicente Grau
Global single-valued biomarkers of cardiac function typically used in clinical practice, such as ejection fraction, provide limited insight on the true 3D cardiac deformation proce…
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Marcel Beetz, Abhirup Banerjee, Julius Ossenberg-Engels +1
Cine magnetic resonance imaging (MRI) is the current gold standard for the assessment of cardiac anatomy and function. However, it typically only acquires a set of two-dimensional…
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks
Marcel Beetz, Yilong Yang, Abhirup Banerjee +2
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases with associated clinical decision-making typically based on single-valued imaging biomarkers. Howeve…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Deep Computational Model for the Inference of Ventricular Activation Properties
Lei Li, Julia Camps, Abhirup Banerjee +3
Patient-specific cardiac computational models are essential for the efficient realization of precision medicine and in-silico clinical trials using digital twins. Cardiac digital t…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…