10 citations · 14 across the 4 of their papers we have counts for
5 papers
Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events
Paula Feldman, Nusrat Binta Nizam, Sunwoo Kwak +3
Cardiovascular disease (CVD) remains the leading cause of death among women, yet cardiovascular risk assessment often relies on clinical variables that may be missing, outdated, or…
GeoPose: Patient-agnostic CTA-to-DSA registration through projection-space calibration
Rudolf L. M. van Herten, Robert Graf, Paula Feldman +1
Aligning intraoperative biplanar digital subtraction angiography (DSA) to pre-procedural computed tomography angiography (CTA) requires rapid and accurate 3D-to-2D registration. Op…
VesselGPT: Autoregressive Modeling of Vascular Geometry
Paula Feldman, Martin Sinnona, Claudio Delrieux +2
Anatomical trees are critical for clinical diagnosis and treatment planning, yet their complex and diverse geometry make accurate representation a significant challenge. Motivated…
Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Paula Feldman, Miguel Fainstein, Viviana Siless +2
Anatomical trees play an important role in clinical diagnosis and treatment planning. Yet, accurately representing these structures poses significant challenges owing to their intr…
VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis
Paula Feldman, Miguel Fainstein, Viviana Siless +2
We present a data-driven generative framework for synthesizing blood vessel 3D geometry. This is a challenging task due to the complexity of vascular systems, which are highly vari…