11 citations · 11 across the 4 of their papers we have counts for
4 papers
Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights
Cosmin-Andrei Hatfaludi, Alex Serban
Federated learning has the potential to unlock siloed data and distributed resources by enabling collaborative model training without sharing private data. As more complex foundati…
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-…
Generative 3D Cardiac Shape Modelling for In-Silico Trials
Andrei Gasparovici, Alex Serban
We propose a deep learning method to model and generate synthetic aortic shapes based on representing shapes as the zero-level set of a neural signed distance field, conditioned by…
Deep learning based detection of collateral circulation in coronary angiographies
Cosmin-Andrei Hatfaludi, Daniel Bunescu, Costin Florian Ciusdel +9
Coronary artery disease (CAD) is the dominant cause of death and hospitalization across the globe. Atherosclerosis, an inflammatory condition that gradually narrows arteries and ha…