3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound
Jakob Ambsdorf, Asbjørn Munk, Sebastian Llambias +6
With access to large-scale, unlabeled medical datasets, researchers are confronted with two questions: Should they attempt to pretrain a custom foundation model on this medical dat…
A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
Stefano Cerri, Asbjørn Munk, Sebastian Nørgaard Llambias +11
We present FOMO260K, a large-scale, heterogeneous dataset of 260,927 brain Magnetic Resonance Imaging (MRI) scans from 77,589 MRI sessions and 55,378 subjects, aggregated from 910…
Revisiting CLIP: Efficient Alignment of 3D MRI and Tabular Data using Domain-Specific Foundation Models
Jakob Krogh Petersen, Valdemar Licht, Mads Nielsen +1
Multi-modal models require aligned, shared embedding spaces. However, common CLIP-based approaches need large amounts of samples and do not natively support 3D or tabular data, bot…