3 papers
cs.CV2025
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…
cs.CV2025
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-…
cs.CV2024
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…