5 citations · 6 across the 3 of their papers we have counts for
4 papers
MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance
Hallee E. Wong, Jose Javier Gonzalez Ortiz, John Guttag +1
Medical researchers and clinicians often need to perform novel segmentation tasks on a set of related images. Existing methods for segmenting a new dataset are either interactive,…
Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis
Neel Dey, Benjamin Billot, Hallee E. Wong +5
Current volumetric biomedical foundation models struggle to generalize as public 3D datasets are small and do not cover the broad diversity of medical procedures, conditions, anato…
Tyche: Stochastic In-Context Learning for Medical Image Segmentation
Marianne Rakic, Hallee E. Wong, Jose Javier Gonzalez Ortiz +3
Existing learning-based solutions to medical image segmentation have two important shortcomings. First, for most new segmentation task, a new model has to be trained or fine-tuned.…
ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image
Hallee E. Wong, Marianne Rakic, John Guttag +1
Biomedical image segmentation is a crucial part of both scientific research and clinical care. With enough labelled data, deep learning models can be trained to accurately automate…