{"ID":6138184,"CreatedAt":"2026-07-09T01:07:32.349475501Z","UpdatedAt":"2026-07-11T09:50:00.969502845Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.07219","arxiv_id":"2607.07219","title":"Vision Foundation Models in Radiology: A Scoping Review of Data, Methodology, Evaluation and Clinical Translation","abstract":"Vision foundation models (VFMs) are increasingly being developed for radiological imaging, yet their definition, development and evaluation remain heterogeneous. We conducted a PRISMAScR scoping review of peer-reviewed studies published between January 2017 and March 2026 describing foundation models trained exclusively on radiological imaging data. Sixty-seven studies were included and mapped across three pillars: data scale and heterogeneity, architectural and pretraining scalability, and downstream transferability and generalization. Datasets primarily covered brain MRI, thoracoabdominal CT, and chest X-ray, ranging from fewer than 100,000 samples to multi-million-image cohorts. Transformer-based architectures and self-supervised pretraining predominated, particularly masked image modeling, contrastive learning and multi-stage approaches. Evaluation focused mainly on segmentation and classification, whereas cross-center, cross-scanner, anatomical and modality-shift validation was inconsistently reported. Alignment with FUTURE-AI principles was uneven. Overall, radiology-specific VFMs show promising transferability, but clinical translation remains constrained by limited data representativeness, heterogeneous benchmarks, incomplete reporting and insufficient deployment-oriented evaluation.","short_abstract":"Vision foundation models (VFMs) are increasingly being developed for radiological imaging, yet their definition, development and evaluation remain heterogeneous. We conducted a PRISMAScR scoping review of peer-reviewed studies published between January 2017 and March 2026 describing foundation models trained exclusivel...","url_abs":"https://arxiv.org/abs/2607.07219","url_pdf":"https://arxiv.org/pdf/2607.07219v1","authors":"[\"Alejandro Vergara-Richart\",\"Xavier Rafael-Palou\",\"Almudena Fuster-Matanzo\",\"Ignacio Iborra Roncales\",\"Ángel Alberich-Bayarri\",\"Ana Jiménez-Pastor\"]","published":"2026-07-08T10:01:33Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\",\"cs.LG\"]","methods":"[\"Transformer\"]","has_code":false}