Call for Papers

We invite contributions to the 8th edition of Medical Imaging with Deep Learning (MIDL 2025), to be held in Salt Lake City, Utah, USA, from July 9–11, 2025. This premier event brings together deep learning researchers, clinicians, and healthcare industry professionals to explore the frontier of machine learning in medical image analysis. MIDL 2025 will offer both in-person attendance and free online streaming.

This year, we are pleased to announce a dual emphasis on both advanced methodological papers and clinically focused papers that showcase the application of cutting-edge AI techniques in addressing clinical challenges and translating these methods into practice. We encourage submissions that demonstrate robust validation studies and clinical relevance alongside novel methodological advances.

MIDL has a large scope including all areas where deep learning is used to analyze biomedical imaging data. Topics of interest include but are not limited to:

• Segmentation of medical images
• Learning-based image registration
• Computer-aided detection and diagnosis
• Image acquisition and reconstruction
• Transfer learning and domain adaptation
• Learning with noisy labels and limited data
• Unsupervised deep learning and representation learning
• Uncertainty quantification
• Interpretability and explainable AI
• Integration of imaging and clinical data
• Multimodal learning combining imaging with textual data and other data types
• Foundation models for medical imaging
• Generative AI for medical imaging
• Federate learning for medical imaging
• Safe and trustworthy learning-assisted solutions for medical imaging
• Validation studies and deep learning applications across various medical specialties such as radiology, pathology, endoscopy, dermatology, ophthalmology, and more.

Inquiries to the chairs can be addressed directly to [email protected].

Submission Guidelines

Please note that this year, reviews will be single-blind, and papers substantially similar to other submissions or previously accepted works are not permissible.

Conference submissions follow two tracks: full conference papers and short papers.

Full Papers

Submissions should either contain significant methodological developments or well-validated applications of deep learning in medical imaging. Full papers are limited to 8 pages, excluding references, acknowledgements, and appendices. There are no page limits for the references and appendices. However, reviewers are not required to read the appendices to evaluate a submission. Full papers will undergo a rigorous review process and will be published in the Proceedings of Machine Learning Research. Selected papers will be invited for oral presentation. At least one co-author must present in person.

Short Papers

These submissions are limited to 3 pages, excluding references. Short papers may present novel methodological ideas without extensive validation or discuss recently published or submitted journal contributions, providing an opportunity for feedback. The review process for short papers will be lighter, and all accepted submissions will be presented at the conference.

Paper Template and Submission Platform

Details about the submission template and instructions can be here. Submissions should be made through OpenReview.

For inquiries, please contact the program chairs at [email protected].

Join us at MIDL 2025 to share insights, forge collaborations, and push the boundaries of medical imaging with deep learning. We look forward to your innovative contributions and to welcoming you in Salt Lake City!

Submission Timeline

All deadlines are 23:59 UTC-12/Anywhere on Earth (AoE).

Note that visa invitation letters will be available on request as soon as a valid paper has been submitted. Please contact the organizers at [email protected]

While the title and abstract can still be changed after the registration deadline (until the submission deadline), they will be used to assign the papers to the reviewers. The authors are therefore asked to give meaningful names and abstracts.

Full Papers

Full Paper OpenReview Platform

Short Papers

Short Paper OpenReview Platform

Conference Dates