vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation

TL;DR

vesselFM is a universal foundation model that achieves zero-shot generalization for 3D blood vessel segmentation across multiple imaging modalities, reducing the need for extensive annotations and domain-specific training.

Contribution

This work introduces vesselFM, a novel foundation model specifically designed for 3D blood vessel segmentation that generalizes well to unseen domains and modalities.

Findings

VesselFM outperforms existing models in multiple imaging modalities.

The model achieves high accuracy in zero-shot, one-shot, and few-shot scenarios.

It reduces the need for extensive dataset-specific annotations.

Abstract

Segmenting 3D blood vessels is a critical yet challenging task in medical image analysis. This is due to significant imaging modality-specific variations in artifacts, vascular patterns and scales, signal-to-noise ratios, and background tissues. These variations, along with domain gaps arising from varying imaging protocols, limit the generalization of existing supervised learning-based methods, requiring tedious voxel-level annotations for each dataset separately. While foundation models promise to alleviate this limitation, they typically fail to generalize to the task of blood vessel segmentation, posing a unique, complex problem. In this work, we present vesselFM, a foundation model designed specifically for the broad task of 3D blood vessel segmentation. Unlike previous models, vesselFM can effortlessly generalize to unseen domains. To achieve zero-shot generalization, we train vesselFM on three heterogeneous data sources: a large, curated annotated dataset, data generated by a domain randomization scheme, and data sampled from a flow matching-based generative model. Extensive evaluations show that vesselFM outperforms state-of-the-art medical image segmentation foundation models across four (pre-)clinically relevant imaging modalities in zero-, one-, and few-shot scenarios, therefore providing a universal solution for 3D blood vessel segmentation.