Elazer R Edelman — accepted AI-conference papers

2026

Anatomica: Localized Control over Geometric and Topological Properties for Anatomical Diffusion Models

Karim Kadry, Abdalla Abdelwahed, Ajay Manicka, Naravich Chutisilp, Farhad R. Nezami, Elazer R. Edelman

CVPR 2026

Controllable generation of anatomical structures enables the rational design of synthetic datasets for virtual simulation trials and machine learning workflows. We present an inference-time guidance framework for generating 3D multi-class anatomical segmentations with localized geometric and topolog

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2026

CardioComposer: Leveraging Differentiable Geometry for Compositional Control of Anatomical Diffusion Models

Karim Kadry, Shoaib A. Goraya, Ajay Manicka, Abdalla Abdelwahed, Naravich Chutisilp, Farhad R. Nezami +1

ICLR 2026poster

Generative models of 3D cardiovascular anatomy can synthesize informative structures for clinical research and medical device evaluation, but face a trade-off between geometric controllability and realism. We propose CardioComposer: a programmable, inference-time framework for generating multi-class…

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2024

A Diffusion Model for Simulation Ready Coronary Anatomy with Morpho-skeletal Control

Karim Kadry*, Shreya Gupta, Jonas Sogbadji, Michiel Schaap, Kersten Petersen, Takuya Mizukami +3

ECCV 2024poster

"Virtual interventions enable the physics-based simulation of device deployment within coronary arteries. This framework allows for counterfactual reasoning by deploying the same device in different arterial anatomies. However, current methods to create such counterfactual arteries face a trade-off…

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