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After a hiatus of two years, we will hold the 4th edition of the Breast Image Analysis (BIA) workshop in conjunction with MICCAI 2018. The aim of BIA is to bring together the growing number of researchers in the field given the significant amount of effort in the development of tools that can automate the analysis and synthesis of breast imaging. The main purpose of the workshop is to provide a stimulating environment for an in-depth discussion of important recent developments among experts in the field that enables future research impact in the field.

Proceedings published by SPRINGER under the “Lecture Notes in Computer Science” book series.

Authors will be invited to contribute to a chapter in a book about Breast Image Analysis.

Topics included but not limited to:

  • Computer-aided detection and diagnosis of breast cancer
  • Models for breast deformation
  • Multi-modality breast image registration, analysis, and fusion
  • Quantitative analysis of breast imaging modalities
  • Predicting and measuring response to treatment
  • Planning, simulation, and guidance for breast surgery and outcome prediction
  • Relating imaging biomarkers to risk factors and non-imaging information
  • Research related to the elucidation and improvement of clinical workflows
  • Breast density and parenchymal pattern analysis and risk assessment
  • Large scale breast image screening and analysis

Important Dates

  1. May 18th: results released for MICCAI’18 papers 
  2. NEW! ->  June 18th (11.59pm PST): BIA'18 paper submission deadline  <- NEW!
  3. July 11th: BIA'18 paper notification of acceptance
  4. July 17th: BIA'18 Camera-ready version submission
  5. Workshop Day: September 16th (AM Session at  "Press Room" at the Conference Center)

Submission Guidelines

● BIA uses the same guidelines as MICCAI'18 main conference submissions. Find them in MICCAI Author's Guide.
● Papers should be formatted in Lecture Notes in Computer Science style. Template can be found HERE. The file format for submissions is Adobe Portable Document Format (PDF). Other formats will not be accepted.
● The maximum number of pages is 8. Submissions exceeding this limit will be rejected without review.
● You should not modify any of the formatting commands in the style files. Any modifications found may result in automatic rejection.
● The review process is double blind. Submissions are to be fully anonymized.
● It is also possible to submit supplementary material with your submission (see section 5 of MICCAI Author's Guide for more information about the format). The deadline for submitting the supplementary material is the same as for the main paper.

Keynote Speakers


Anne Martel, Ph.D
Sunnybrook Health Sciences Centre

"Computer-aided detection and diagnosis of breast cancer with MRI"

Orcun Goksel, M.A.Sc, Ph.D
ETH Zurich


 "Ultrasound: An age-old ingredient, for new recipes in medical imaging"

William Lotter, Ph.D
Harvard University
DeepHealth Inc.

"Towards Clinically Viable AI for Screening Mammography"


9:30am - 9:45am

Opening Remarks

9:45am - 10:30am

Invited Talk by Orcun Goksel

Ultrasound: An age-old ingredient, for new recipes in medical imaging

10:30am - 11:00

Spotlight Presentations

Siamese Network for Dual-View Mammography
Mass Matching
Shaked Perek, Alon Hazan, Ella Barkan,
Ayelet Akselrod-Ballin

Large-scale mammography CAD with
Deformable Conv-Nets
Stephen Morrell, Zbigniew Wojna, Can Son Khoo, Sebastien Ourselin, Juan Eugenio Iglesias

Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on
Diffusion-Weighted MR Images
Jennifer Kamphenkel, Paul F. Jager, Sebastian Bickelhaupt, Frederik Bernd Laun , Wolfgang Lederer, Heidi Daniel, Tristan Anselm Kuder, Stefan Delorme, Heinz-Peter Schlemmer, Franziska Konig,
Klaus H. Maier-Hein

Reproducible evaluation of registration algorithms for movement correction in dynamic contrast enhancing magnetic resonance imaging for
breast cancer diagnosis
I. A. Illan, J. Ramirez, J. M. Gorriz, K. Pinker, A. Meyer-Baese

Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net
Heyi Li, Dongdong Chen, William H. Nailon,
Mike E. Davies, David Laurenson

Improving Breast Cancer Detection using Symmetry Information with Deep Learning
Yeman Brhane Hagos, Albert Gubern Merida,
Jonas Teuwen

Conditional Infilling GANs for Data Augmentation in Mammogram Classification
Eric Wu, Kevin Wu, David Cox, William Lotter

A Unified Mammogram Analysis Method via Hybrid Deep Supervision
Rongzhao Zhang, Han Zhang, Albert C.S. Chung

Structure-aware Staging for Breast Cancer Metastases
Songtao Zhang, Li Sun, Ruiqiao Wang, Hongping Tang, Jin Zhang, Lin Luo

11:00 - 11:30

Poster Presentations + Coffee Break

11:30 - 12:15

Invited Talk by Anne Martel

Computer-aided detection and diagnosis of breast cancer with MRI

12:15 - 13:00

Invited Talk by William Lotter

Towards Clinically Viable AI for Screening Mammography

13:00 - 13:10

Best Paper Award Ceremony and
Closing Remarks

13:10 - 13:30

Poster Presentations


The University of Adelaide

The University of Adelaide

The University of Queensland

Instituto Superior Tecnico

The University of Queensland

Program Committee

Adrian Barbu, Florida State University
Amir Jamaludin, University of Oxford
Anne Martel, Sunnybrook Research Institute
Carlos Arteta, University of Oxford
Dario Oliveira, IBM Research
Gerard Snaauw, The University of Adelaide
Gregory Slabaugh, Huawei Research and Development
Hayden Faulkner, The University of Adelaide
Helder Oliveira, Universidade do Porto
João Teixeira, Universidade do Porto
Jonas Teuwen, Radboud University Medical Center
Kelwin Fernandes, Universidade do Porto
Lisa Tang, University of British Columbia
Manuel Marques, Instituto Superior Tecnico de Lisboa
Mehmet Aygün, Istanbul Technical University
Nishikant Deshmukh, Johns Hopkins University
Prasad Sudhakar, GE Global Research
Roger Tam, University of British Columbia
Saad Ullah Akram, University of Oulu, Finland
Shadi Albarqouni, Technische Universität München
Sílvia Bessa, Universidade do Porto
Steffen Schneider, RWTH-Aachen University
Takayuki Kitasaka, Aichi Institute of Technology
Tao Tan, Eindhoven University of Technology
Thomas Papastergiou, University of Patras
Weidong Cai, University of Sydney
Yong Xia, Northwestern Polytechnical University
Ziyue Xu, National Institutes of Health

Countdown to BIA Workshop

16/09/2018 - BIA Workshop

Help Us to Promote BIA'18!

Important Dates

Submission: 18/06/18
Notification: 11/07/18