activity
20202023
most citedEchocardiogram Foundation Model -- Application 1: Estimating Ejection Fraction

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20244 cited

SurGen: Text-Guided Diffusion Model for Surgical Video Generation

Joseph Cho, Samuel Schmidgall, Cyril Zakka +4

Diffusion-based video generation models have made significant strides, producing outputs with improved visual fidelity, temporal coherence, and user control. These advancements hol…

eess.IV20231 cited

Echocardiogram Foundation Model -- Application 1: Estimating Ejection Fraction

Adil Dahlan, Cyril Zakka, Abhinav Kumar +4

Cardiovascular diseases stand as the primary global cause of mortality. Among the various imaging techniques available for visualising the heart and evaluating its function, echoca…

cs.CV2021

Simulating time to event prediction with spatiotemporal echocardiography deep learning

Rohan Shad, Nicolas Quach, Robyn Fong +8

Integrating methods for time-to-event prediction with diagnostic imaging modalities is of considerable interest, as accurate estimates of survival requires accounting for censoring…

cs.CV2021

Predicting post-operative right ventricular failure using video-based deep learning

Rohan Shad, Nicolas Quach, Robyn Fong +17

Non-invasive and cost effective in nature, the echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves. Despite progressive improvements over the…

q-bio.TO2020

A Design-Based Model of the Aortic Valve for Fluid-Structure Interaction

Alexander D. Kaiser, Rohan Shad, William Hiesinger +1

This paper presents a new method for modeling the mechanics of the aortic valve, and simulates its interaction with blood. As much as possible, the model construction is based on f…