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

Will be a workshop at MICCAI 2024, 6-10 October, Marrakesh, Morocco.

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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.
responsive devices

Recent Updates

Program

The following is a tentative program:

Location: Marrakesh, Morocco

Our amazing keynote speakers are coming soon ...

About Us

Deep-Brea3th 2024: A Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care

The Deep-Breath2024 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 should 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 two 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.
  • 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.

    • Submissions for both tracks should be submitted via the CMT system: https://cmt3.research.microsoft.com/DeepBreath2024

    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.

    Join us to share your academic achievements

    Use AI to change the future with domain experts

    Submit now!

    Important Dates

    • April 1, 2024 Open individual websites
    • May 13, 2024 Open for submissions
    • June 24, 2024 Paper Submission Deadline
    • July 18, 2024 Notification of Paper Decision
    • July 31, 2024 Camera-ready Deadline
    • July 31, 2024 Full Program Available
    • Oct 10, 2024 Workshop!
    • Sedna Testimonial Avatar

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

      Ritse Mann, Radiologist.

    • 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-BREATH2024 Committee

    Organizing Committee

    Tianyu Zhang (co-chair)

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

    Tao Tan (co-chair)

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

    Daniel Truhn

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

    Shuo Li

    School of Biomedical Engineering, Case Western Reserve University, Cleveland, USA

    Yuan Gao

    GROW, Maastricht University, Maastricht, the Netherlands

    Shannon Doyle

    Netherlands Cancer Institute, Amsterdam, the Netherlands

    Robert Marti Marly

    Computer Technology, University of Girona, Spain

    Jakob Nikolas Kather

    Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany

    Katja Pinker-Domenig

    Department of Radiology, Memorial Sloan Kettering Cancer Center, USA

    Shandong Wu

    Department of Radiology, University of Pittsburgh, Pittsburgh, USA

    Geert Litjens

    Digital Pathology, RadboudUMC, Nijmegen, the Netherlands

    Ritse Mann (in-chief)

    Breast Imaging Group, RadboudUMC, Nijmegen, the Netherlands

    Technical Committee

    Luyi Han (Medical Imaging Department, RadboudUMC, Nijmegen, the Netherlands)
    Xin Wang (Radiology Department, NKI, Amsterdam, the Netherlands)
    Chunyao Lu (Medical Imaging Department, RadboudUMC, Nijmegen, the Netherlands)
    Xinglong Liang (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Cheng Lu (Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, China)
    Ehsan Kozegar (University of Guilan, Iran)
    Xiaohong Liu (Shanghai Jiao Tong University, Shanghai, China)
    Menghan Hu (East China Normal University, China)
    Nika Rasoolzadeh (BIG, RadboudUMC, Nijmegen, the Netherlands)
    Jarek van Dijk (BIG, RadboudUMC, Nijmegen, the Netherlands)

    Clinical Committee

    Antonio Portaluri (Department of Biomedical Sciences and Morphologic and Functional Imaging, University of Messina, Sicily, Italy)
    Carla Sitges (Hospital Clínic de Barcelona, Barcelona, Spain)
    Anna D'Angelo (Department of Diagnostic Imaging, Oncological Radiotherapy and Haematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy)

    Coming soon...

    Contact

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

                                       

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