Deep-Breath 2026 is a workshop affiliated with MICCAI 2026 in Strasbourg, France, focused on advancing AI and imaging research for diagnostic and treatment challenges in breast cancer. It brings together clinicians, AI experts, and researchers to share innovations in multimodal imaging, machine learning, and clinical applications, with an emphasis on reproducibility, collaboration, and real-world impact.
A strong submission should clearly identify its contribution and evaluate it appropriately.
Full papers
New, original work submitted in PDF format following LNCS guidelines; up to 8 pages of text, figures, and tables plus up to 2 pages of references; subject to double-blind peer review; accepted papers published in MICCAI Satellite LNCS proceedings and may be recommended to high-impact journals.
Abstracts
New or recently published/accepted work limited to 2500 characters including spaces, structured under Purpose, Materials and Methods, Results, Conclusion; a figure is recommended; accepted abstracts made publicly accessible on the workshop website.
Research areas in scope
01
AI and Imaging in Breast Cancer
Breast imaging (mammography, ultrasound, MRI, PET/CT, H&E, etc.)Detection, segmentation and classificationBreast cancer screeningHistological characteristicsMedical image registrationMultimodal imaging fusionImage synthesisImage reconstructionRisk assessment and predictionTreatment responseDrug selectionLymph node statusMolecular subtypesTumor microenvironmentPrediction of cancer recurrenceReader studyPathologyRadiologyNatural language processingLLMsFederated learningSwarm learning
Policies worth checking twice
Submissions must be double-blind: author identities must be anonymized.
Full papers are limited to 8 pages of content plus 2 pages of references.
Abstracts are limited to 2500 characters including spaces.
All submissions must be original work (for full papers); abstracts may be based on recently published/accepted work.
Accepted papers require completion and signing of a Consent-to-Publish form by the corresponding/senior author.
All code for accepted papers must be made publicly available to ensure reproducibility.
Submissions are handled via OpenReview.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.