4 citations · 8 across the 6 of their papers we have counts for
6 papers
EchoVLM: Measurement-Grounded Multimodal Learning for Echocardiography
Yuheng Li, Yue Zhang, Abdoul Aziz Amadou +5
Echocardiography is the most widely used imaging modality in cardiology, yet its interpretation remains labor-intensive and inherently multimodal, requiring view recognition, quant…
ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies
Costin F. Ciusdel, Alex Serban, Tiziano Passerini
While traditional self-supervised learning methods improve performance and robustness across various medical tasks, they rely on single-vector embeddings that may not capture fine-…
EchoApex: A General-Purpose Vision Foundation Model for Echocardiography
Abdoul Aziz Amadou, Yue Zhang, Sebastien Piat +4
Quantitative evaluation of echocardiography is essential for precise assessment of cardiac condition, monitoring disease progression, and guiding treatment decisions. The diverse n…
Graph convolutional regression of cardiac depolarization from sparse endocardial maps
Felix Meister, Tiziano Passerini, Chloé Audigier +6
Electroanatomic mapping as routinely acquired in ablation therapy of ventricular tachycardia is the gold standard method to identify the arrhythmogenic substrate. To reduce the acq…
Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks
Felix Meister, Tiziano Passerini, Viorel Mihalef +3
To date, the simulation of organ deformations for applications like therapy planning or image-guided interventions is calculated by solving the elastodynamics equations. While effi…
Deep Neural Networks for ECG-free Cardiac Phase and End-Diastolic Frame Detection on Coronary Angiographies
Costin Ciusdel, Alexandru Turcea, Andrei Puiu +10
Invasive coronary angiography (ICA) is the gold standard in Coronary Artery Disease (CAD) imaging. Detection of the end-diastolic frame (EDF) and, in general, cardiac phase detecti…