Vision Foundation Models for Computed Tomography

Understand

Foundation models (FMs) have shown transformative potential in radiology by performing diverse, complex tasks across imaging modalities.

• Here, we developed CT-FM, a large-scale 3D image-based pre-trained model designed explicitly for various radiological tasks.
• CT-FM was pre-trained using 148,000 computed tomography (CT) scans from the Imaging Data Commons through label-agnostic contrastive learning.
• We evaluated CT-FM across four categories of tasks, namely, whole-body and tumor segmentation, head CT triage, medical image retrieval, and semantic understanding, showing superior performance against state-of-the-art models.