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DEF-AI-MIA 2024 : Workshop on Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis & 4th COV19D Competition @ IEEE CVPR 2024

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Link: https://ai-medical-image-analysis.github.io/4th/
 
When Jun 17, 2024 - Jun 21, 2024
Where Seattle, USA
Submission Deadline Mar 23, 2024
Notification Due Apr 7, 2024
Final Version Due Apr 14, 2024
Categories    medical image analysis   fairness & explainability   domain adaptation   ai, machine & deep learning
 

Call For Papers

Dear Colleagues,

We are inviting you to participate in the Domain adaptation, Explainability and Fairness in AI for Medical Image Analysis (DEF-AI-MIA) Workshop and 4th COV19D Competition to be held in conjunction with the IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2024 in Seattle, USA, 17 – 21 June, 2024.


A) In the past few years, Deep Learning techniques have made rapid advances in many medical image analysis tasks. In pathology and radiology applications, they managed to increase the accuracy and precision of medical image assessment, which is often considered subjective and not optimally reproducible. This is due to the fact that they can extract more clinically relevant information from medical images than what is possible in current routine clinical practice by human assessors. Nevertheless, considerable development and validation work lies ahead before AI-based methods can be fully integrated ad used in routine clinical tasks.

Of major importance is research on domain adaptation, fairness and explainability in AI-enabled medical image analysis. This research constitutes the main target of the DEF-AI-MIA Workshop. The workshop aims to foster discussion and presentation of ideas to tackle these challenges in the field, as well as identify research opportunities in this context. More information can be found here.


Important Dates:

March 23, 2024: Paper submission
April 7, 2024: Review decisions sent to authors; notifications of acceptance
April 14, 2024: Camera ready version

For any requests or enquiries, please contact: stefanos@cs.ntua.gr


B) The 4th COV19D Competition includes two Challenges: i) Covid-19 Detection Challenge and ii) Covid-19 Domain Adaptation Challenge.
The 1st Challenge refers to detection of COVID-19 in chest 3D CT scans obtained from a single source, i.e., hospital. The 2nd Challenge refers to detection of COVID-19 in chest 3D CT scans obtained from various sources, i.e., hospitals with different data distributions.


Important Dates:

January 8, 2024: Opening of the Competition
March 16, 2024: Submission of results
March 19, 2024: Winners announcement
March 23, 2024: Paper submission
April 7, 2024: Review decisions sent to authors; notifications of acceptance
April 14, 2024: Camera ready version


For registration and further information, please contact d.kollias@qmul.ac.uk


General Chairs:

Stefanos Kollias (National Technical University of Athens)
Dimitris N. Metaxas (Rutgers University)


Program Chairs:

Dimitrios Kollias (Queen Mary University London)
Xujiong Ye (University of Lincoln)
Francesco Rundo (STMicroelectronics ADG—Central R&D)


All accepted papers will be part of IEEE CVPR 2024 Conference Proceedings.



Kind Regards,
on behalf of the organising committee,
Dimitrios Kollias

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