Deep-Brea3th 2025: 2nd Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care

Will be a workshop at MICCAI 2025, 23-27 September, Daejeon, South Korea.

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Breast Cancer
Breast cancer is the most common malignant tumor in women and has a high degree of heterogeneity.
Multimodal Imaging
Medical imaging techniques plays an integral role in the detection and characterization of breast cancer.
Artificial Intelligence
Artificial Intelligence has reignited the interest in automated breast image interpretation.

Deep-Breath will drive your research forward

Present your academic research in a beautiful way. Meet with domain experts to explore potential collaboration opportunities.
  • Efficient & Repeatable
    High-quality peer review, all codes will be made public for scholars to reproduce and promote.
  • Share & Communicate
    Share your research and interact with scholars in the same field.
  • Focused & Broad
    Focuses on breast field and covers hot topics in a wide range of areas including pathology, radiology, artificial intelligence and more.
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Program

The following is the final program:

23 September (full-day) 2025, MICCAI 2025, Daejeon, South Korea

Daejeon Convention Center, Meeting Room: IBS-2F-100

Download Deep-Breath 2025 Program

Join Our Three Associated Challenges at the Workshop

  • ODELIA 2025: ODELIA BREAST MRI Challenge 2025.
  • MAMA-MIA 2025: Advancing Generalizability and Fairness in Breast MRI Tumour Segmentation and Treatment Response Prediction.
  • UUSIC 2025: Universal Ultrasound Image Challenge: Multi-Organ Classification and Segmentation.

    • About Us

    Deep-Brea3th 2025: 2nd Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care

    The Deep-Breath2025 workstation will provide a discussion forum focused on the topic of AI in breast cancer and aims to promote the development of related research areas, to share insights in academic research and clinical practice among clinicians and AI experts, and explore the opportunities and address potential challenges of AI applications in breast health, thus potentially benefiting doctors and patients. The workshop will publish original papers in all areas related to the AI in breast cancer arena including, but not limited to, the following suggested topics:

  • Breast imaging (mammography, ultrasound, MRI, PET/CT, H&E, etc.)
  • Detection, segmentation and classification
  • Breast cancer screening
  • Histological characteristics
  • Medical image registration
  • Multimodal imaging fusion
  • Image synthesis
  • Image reconstruction
  • Risk assessment and prediction
  • Treatment response
  • Drug selection
  • Lymph node status
  • Molecular subtypes
  • Tumor microenvironment
  • Prediction of cancer recurrence
  • Radiomics
  • Reader study
  • Pathology
  • Radiology
  • Natural language processing
  • LLMs
  • Federated learning
  • Swarm learning
  • ...

    • Manuscript Preparation and Submission

    Submissions may be in two tracks:

  • Track 1. Full papers: Submissions must be new work. Papers must be submitted electronically in searchable pdf format following the guidelines for authors and LaTeX and MS Word templates available at Lecture Notes in Computer Science (LNCS). Manuscripts can be up to 8-pages (text, figures and tables) plus up to 2 pages of references. The MICCAI Conference review process is double-blind, i.e. the names of the authors, reviewers, and area chairs are not revealed to each other. Papers must thus be properly anonymized before submission. All submissions will be reviewed by at least three experts with experience of relevance. Accepted papers will be assigned for oral or poster presentation based on review scores, and will be published by Springer Nature as a part of the MICCAI Satellite Events joint LNCS proceedings. For accepted papers, the corresponding/senior authors will need to complete and sign a Consent-to-Publish form on behalf of all the authors. Importantly, after review, some papers will be recommended to high-impact partner journals (indexed by SCI).
  • Track 2. Abstracts: Submissions may be new work or recently published/accepted papers. Abstracts are limited to 2500 characters including spaces, and are to be constructed using the following section headings: Purpose; Materials and Methods; Results; Conclusion. It is recommended that a figure to support your work accompany your submission. Accepted abstracts will be assigned for oral or poster presentation based on review scores, and made publicly accessible on this website.

    • Among all the accepted full papers and abstracts, Deep-Breath will give a Best Student Paper award, a Best Workshop Paper award, and a Best Abstract Award, all with electronic certificates.

    Submissions for both tracks should be submitted via the CMT system: https://cmt3.research.microsoft.com/DeepBreath2025

    Acknowledgment: The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

    Join us to share your academic achievements

    Use AI to change the future with domain experts

    Submit now!

    Important Dates

    • April 1, 2025 Open individual websites
    • May 13, 2025 Open for submissions
    • June 25 July 15, 2025 Paper Submission Deadline
    • July 23, 2025 Notification of Paper Decision
    • July 30, 2025 Camera-ready Deadline
    • August 1, 2025 Full Program Available
    • August 15, 2025 Workshop proceedings due
    • Sep 23&27, 2025 Workshop!
    • Sedna Testimonial Avatar

      "AI will eventually replace radiologists in screen-reading."

      Ritse Mann, Radiologist.

    • Sedna Testimonial Avatar

      "By using swarm learning across international MRI datasets, we are enhancing AI-driven detection of early breast cancer patterns. Our reserach will allow more precise and equitable screening outcomes."

      Jakob Nikolas Kather, physician/scientist.

    • Sedna Testimonial Avatar

      "Tomorrow’s best radiologists won’t just diagnose – they’ll debug algorithms."

      Alexandra Athanasiou, Radiologist.

    • Sedna Testimonial Avatar

      "AI tools have a key role to play in the future of breast screening."

      Fiona Gilbert, Radiologist.

    • Sedna Testimonial Avatar

      "With over 2.3M new breast cancer cases annually, AI will be essential in delivering faster, more accurate, and personalized patient care."

      Firas Khader, AI Scientist.

    • Sedna Testimonial Avatar

      "Every new treatment protocol is a legal opportunity for acquiring data for AI."

      Tao Tan, AI Scientist.

    • Sedna Testimonial Avatar

      "Artificial intelligence will potentially assist doctors and benefit patient care."

      Tianyu Zhang, AI Scientist.

    DEEP-BREATH2025 Committee

    General Chairs

    Tianyu Zhang (Radiology Department/BIG, NKI/RadboudUMC, Amsterdam/Nijmegen, the Netherlands)
    Oliver Lester Saldanha (Else Kroener Fresenius Center for Digital Health, Dresden, Germany)
    Nika Rasoolzadeh (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Tao Tan (Faculty of Applied Sciences, Macao Polytechnic University, Macao, China)
    Jakob Nikolas Kather (Else Kroener Fresenius Center for Digital Health, Dresden University of Technology, Dresden, Germany)
    Ritse Mann (Breast Imaging Group, RadboudUMC, Nijmegen, the Netherlands)

    Organizing Committee

    Tianyu Zhang (chair)

    Radiology Department/BIG, NKI/RadboudUMC, Amsterdam/Nijmegen, the Netherlands

    Oliver Lester Saldanha (co-chair)

    NCT in Uniklinik Heidelberg and EKFZ in TU Dresden, Dresden, Germany

    Nika Rasoolzadeh (co-chair)

    BIG, RadboudUMC, Nijmegen, the Netherlands

    Gustav Müller-Franzes

    Aachen University Hospital, Germany

    Nicholas Payne

    University of Cambridge, UK

    Luyang Luo

    Harvard Medical School, USA

    Yuan Gao

    University Medical Center Utrecht, the Netherlands

    Michael Kalogeropoulos

    Hygeia Hospital, Greece

    Robert Marti Marly

    Computer Technology, University of Girona, Spain

    Daniel Truhn

    Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

    Shandong Wu

    Department of Radiology, University of Pittsburgh, Pittsburgh, USA

    Oliver Diaz

    University of Barcelona, Spain

    Tao Tan

    Faculty of Applied Sciences, Macao Polytechnic University, Macao, China

    Jakob Nikolas Kather

    Else Kroener Fresenius Center for Digital Health, Dresden University of Technology, Dresden, Germany

    Ritse Mann (in-chief)

    Breast Imaging Group, RadboudUMC, Nijmegen, the Netherlands

    Technical Committee

    Behdad Dasht Bozorg (Department of Surgery, NKI, Amsterdam, the Netherlands)
    Lishan Cai (Radiology Department, Netherlands Cancer Institute, Amsterdam, the Netherlands)
    Jarek van Dijk (co-chair in technical committee) (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Ming Fan (Hangzhou Dianzi University, China)
    Luyi Han (co-chair in technical committee) (Medical Imaging Department, RadboudUMC, Nijmegen, the Netherlands)
    Firas Khader (StratifAI, Germany)
    Xinglong Liang (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Zehui Lin (Macao Polytechnic University, China)
    Aitor López (Ribera Salud Hospital, Spain)
    Chunyao Lu (Medical Imaging Department, RadboudUMC, Nijmegen, the Netherlands)
    Adria Marcos (Vall d’Hebron Institute of Oncology, Spain)
    Lidia Garrucho Moras (co-chair in technical committee) (University of Barcelona, Spain)
    Lars Ole Schwen (Fraunhofer Institute for Digital Medicine MEVIS, Germany)
    Xin Wang (Radiology Department, NKI, Amsterdam, the Netherlands)
    Markus Wenzel (Fraunhofer Institute for Digital Medicine MEVIS, Germany)
    Jian Zheng (Chinese Academy of Sciences, China)
    Jiefu Zhu (Dresden University of Technology, Germany)

    Clinical Committee

    Alexandra Athanasiou (Mitera Hospital, Greece)
    Lingyun Bao (Westlake University, China)
    Julia Camps (Ribera Salud Hospital, Spain)
    Anna D'Angelo (Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy)
    Fiona Gilbert (University of Cambridge, UK)
    Ning Mao (Qingdao University, China)
    Raquel Perez-Lopez (Vall d’Hebron Institute of Oncology, Spain)
    Antonio Portaluri (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Ruixiang Qi (Westlake University, China / NKI, the Netherlands)
    Cristina Rossi (University of Zürich, Switzerland)
    Wendelien Sanderink (RadboudUMC, Nijmegen, the Netherlands)
    Carla Sitges (Hospital Clínic de Barcelona, Barcelona, Spain)
    Marialena Tsarouchi (Breast Imaging Group, RadboudUMC, Nijmegen, the Netherlands)
    Wouter Veldhuis (University Medical Center Utrecht, the Netherlands)
    Dong Xu (Chinese Academy of Sciences, China)

    Advisory Board

    Hao Chen (The Hong Kong University of Science and Technology, China)
    Peter Gordebeke (The European Institute for Biomedical Imaging Research (EIBIR), Vienna, Austria)
    Karim Lekadir (Universitat de Barcelona, Spain)
    Shuo Li (Case Western Reserve University, Cleveland, USA)
    Geert Litjens (RadboudUMC, Nijmegen, the Netherlands)
    Ulrike Mayerhofer-Schirmer (The European Institute for Biomedical Imaging Research (EIBIR), Vienna, Austria)

    Contact

    Please contact us for further questions and comments via email at miccai.deepbreath@gmail.com

                                           

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