18 citations · 22 across the 4 of their papers we have counts for
4 papers
ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders
Shawn Xu, Lin Yang, Christopher Kelly +25
In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder combined or grafted onto…
ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans
Felix Lau, Tom Hendriks, Jesse Lieman-Sifry +3
Medical images with specific pathologies are scarce, but a large amount of data is usually required for a deep convolutional neural network (DCNN) to achieve good accuracy. We cons…
Computationally efficient cardiac views projection using 3D Convolutional Neural Networks
Matthieu Le, Jesse Lieman-Sifry, Felix Lau +3
4D Flow is an MRI sequence which allows acquisition of 3D images of the heart. The data is typically acquired volumetrically, so it must be reformatted to generate cardiac long axi…
FastVentricle: Cardiac Segmentation with ENet
Jesse Lieman-Sifry, Matthieu Le, Felix Lau +2
Cardiac Magnetic Resonance (CMR) imaging is commonly used to assess cardiac structure and function. One disadvantage of CMR is that post-processing of exams is tedious. Without aut…