2.2k citations · 5.7k across the 59 of their papers we have counts for
65 papers
GIST: Generating Image-Specific Text for Fine-grained Object Classification
Kathleen M. Lewis, Emily Mu, Adrian V. Dalca +1
Recent vision-language models outperform vision-only models on many image classification tasks. However, because of the absence of paired text/image descriptions, it remains diffic…
AnyStar: Domain randomized universal star-convex 3D instance segmentation
Neel Dey, S. Mazdak Abulnaga, Benjamin Billot +4
Star-convex shapes arise across bio-microscopy and radiology in the form of nuclei, nodules, metastases, and other units. Existing instance segmentation networks for such structure…
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…
Neuralizer: General Neuroimage Analysis without Re-Training
Steffen Czolbe, Adrian V. Dalca
Neuroimage processing tasks like segmentation, reconstruction, and registration are central to the study of neuroscience. Robust deep learning strategies and architectures used to…
Multi-Head Graph Convolutional Network for Structural Connectome Classification
Anees Kazi, Jocelyn Mora, Bruce Fischl +2
We tackle classification based on brain connectivity derived from diffusion magnetic resonance images. We propose a machine-learning model inspired by graph convolutional networks…
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…