27 citations · 38 across the 7 of their papers we have counts for
7 papers
FleXray: Universal Clinical X-ray Segmentation
Victor Ion Butoi, Vivek Gopalakrishnan, John V. Guttag +2
X-ray is medicine's most widely used imaging modality, yet remains among its least quantitative. Unlike volumetric modalities like CT or MRI, X-ray collapses 3D anatomy into a 2D p…
VoxelPrompt: A Vision Agent for End-to-End Medical Image Analysis
Andrew Hoopes, Neel Dey, Victor Ion Butoi +2
We present VoxelPrompt, an end-to-end image analysis agent that tackles free-form radiological tasks. Given any number of volumetric medical images and a natural language prompt, V…
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs
Irene Huang, Wei Lin, M. Jehanzeb Mirza +11
Compositional Reasoning (CR) entails grasping the significance of attributes, relations, and word order. Recent Vision-Language Models (VLMs), comprising a visual encoder and a Lar…
Generative Active Learning for the Search of Small-molecule Protein Binders
Maksym Korablyov, Cheng-Hao Liu, Moksh Jain +31
Despite substantial progress in machine learning for scientific discovery in recent years, truly de novo design of small molecules which exhibit a property of interest remains a si…
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging
Heejong Kim, Victor Ion Butoi, Adrian V. Dalca +2
Most state-of-the-art techniques for medical image segmentation rely on deep-learning models. These models, however, are often trained on narrowly-defined tasks in a supervised fas…
UniverSeg: Universal Medical Image Segmentation
Victor Ion Butoi, Jose Javier Gonzalez Ortiz, Tianyu Ma +3
While deep learning models have become the predominant method for medical image segmentation, they are typically not capable of generalizing to unseen segmentation tasks involving…
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou, Moksh Jain, Hadi Nekoei +5
Epistemic Uncertainty is a measure of the lack of knowledge of a learner which diminishes with more evidence. While existing work focuses on using the variance of the Bayesian post…