Exploring scalable medical image encoders beyond text supervision

Pérez-García, Fernando; Sharma, Harshita; Bond-Taylor, Sam; Bouzid, Kenza; Salvatelli, Valentina; Ilse, Maximilian; Bannur, Shruthi; Castro, Daniel C.; Schwaighofer, Anton; Lungren, Matthew P.; Wetscherek, Maria Teodora; Codella, Noel; Hyland, Stephanie L.; Alvarez-Valle, Javier; Oktay, Ozan

doi:10.1038/s42256-024-00965-w

Cited by 115Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Exploring scalable medical image encoders beyond text supervision

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Pérez-García, Fernando, Sharma, Harshita, Bond-Taylor, Sam, Bouzid, Kenza, Salvatelli, Valentina, Ilse, Maximilian, Bannur, Shruthi, Castro, Daniel C. +7 more·2025·Nature Machine Intelligence

DOI 10.1038/s42256-024-00965-w

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“We compared the performance of In-Context RCA with a single-atlas approach, known to o ﬀ er the strongest results in the classical RCA framework [5], [28].”

A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text?
Silva-Rodríguez, J., Dolz, J., & Ayed, I. B. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-96625-5_20 · Cited by 2 · see citing works
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Lai, Z., Wu, J., Chen, S., Zhou, Y., & Hovakimyan, N. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2403.17343 · Cited by 9 · see citing works
Data Scaling Laws for Radiology Foundation ModelsPreprint
Ilse, M., Sharma, H., Schwaighofer, A., Bond-Taylor, S., Pérez‐García, F., Melnichenko, O., Sykes, A.-M. G., Horst, K. K., Khandelwal, A., Reynolds, M., et al. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2509.12818
Self-citation
QwenCLIP: Boosting Medical Vision-Language Model Pretraining via LLM Embeddings and Prompt Tuning
Wei, X., Kurtz, C., & Cloppet, F. (2026) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi61048.2026.11515750

Authors: Pérez-García, F., Sharma, H., Bond-Taylor, S., Bouzid, K., Salvatelli, V., Ilse, M., Bannur, S., Castro, D. C., Schwaighofer, A., Lungren, M. P., Wetscherek, M. T., Codella, N., Hyland, S. L., Alvarez-Valle, J., & Oktay, O.
Affiliations: Microsoft (United States) (US)
University of Cambridge (GB)
Corresponding author: Sharma, Harshita
ORCID: Pérez-García, Fernando
Sharma, Harshita
Bond-Taylor, Sam
Bouzid, Kenza
Salvatelli, Valentina
Ilse, Maximilian
Bannur, Shruthi
Castro, Daniel C.
Schwaighofer, Anton
Lungren, Matthew P.
Wetscherek, Maria Teodora
Codella, Noel
Hyland, Stephanie L.
Alvarez-Valle, Javier
Oktay, Ozan
Venue: Nature Machine Intelligence
Publisher: Springer Science and Business Media LLC
Published: 2025-01-13
Volume: 7
Issue: 1
Pages: 119-130
ISSN: 2522-5839 (ISSN-L)
DOI: 10.1038/s42256-024-00965-w
OpenAlex: W4406353025
Cited by: 115
References: 103
Citations by year: 2026: 63 · 2025: 46 · 2024: 5
FWCI: 33.15
Type: journal article
Language: en
Open access: green
arxiv.org
Licence: other-oa
www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Nature Machine Intelligence (publishedVersion)
arXiv (Cornell University) (submittedVersion, other-oa)
arXiv (Cornell University)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords: vision-language alignment, medical image classification, semantic segmentation, radiology report generation, privacy leakage, multimodal models

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