22 September 2022

22 September 2022

MICCAI Conference

Medical Applications with Disentanglements (MAD)

đź‘‹ Welcome to the MICCAI MAD Workshop 2022

Generative models are powerful deep learning methods that have demonstrated great potential for applications in the medical domain. Their performance has continuously improved over the last few years. They address several challenges that are due to the lack of sufficient publicly available medical training data, by providing approaches for synthetic dataset creation, unsupervised pre-training, transfer learning, or generation of missing image modalities. However, generative models often generalize poorly, e.g., to data from different domains and are criticized as black boxes due to a lack of interpretability and controllability. Some of these concerns can be handled by analyzing and disentangling the latent space representation of generative models, encouraging a comprehensive, human interpretable, and compressed representation of the data. The goal of this MICCAI workshop is to analyze the different proposed definitions of disentangled representations, review state-of-the-art methods to achieve disentanglement, evaluate and compare existing quality metrics, as well as to discuss new ideas and methods. By considering the mathematical background alongside applied methods, the workshop will combine theory and practice. Furthermore, these foundations will be discussed in the context of present and future medical applications. Results of the workshop and future directions of the disentanglement approach for medical applications are planned to be summarized in a workshop paper.

Overview Papers and Tutorial

(2021). Learning Disentangled Representations in the Imaging Domain.

PDF

(2021). DREAM Tutorial.

Project Video

Call for Papers:

We are looking for papers including:

  • Disentanglement Definitions
  • Disentanglement Metrics
  • Analyzing existing Models or Metrics
  • Application of Disentanglement Methods onto Medical/Clinical Datasets
  • New Disentanglement Models
  • Mathematical Background/Theory

We plan to publish the conference results with Springer Proceedings, thus, please use the template you find here. We accept abstracts (1-2 pages), short paper (3-7 pages) and full paper (8+ pages). Submit you paper here.

The authors of the selected papers will be invited to be co-authors of an overview article, which will be submitted to a top-tier journal.

Submission Deadline: 25 June 22

Acceptance/Revision/Rejection Notification: 16 July 22

Camera ready paper version: 30 July 2022

Best Paper Award

We will provide a price for the best paper.

Keynote Speaker

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Sandy Engelhardt

University Hospital Heidelberg Group Artificial Intelligence in Cardiovascular Medicine (AICM) Heidelberg, Germany

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Yash Sharma

International Max Planck Research School for Intelligent Systems, IMPRS-IS, Tuebingen, Germany

Program Committee

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Alejandro F Frangi

University of Leeds, UK | KU Leuven, Belgium

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Anirban Mukhopadhyay

TU Darmstadt, Germany

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Asja Fischer

Ruhr University Bochum, Germany

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Constantin Seibold

Karlsruhe Institute of Technology, Germany

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Daniel RĂĽckert

Imperial College London, UK | Technical University of Munich, Germany

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Felix Nensa

University Hospital Essen, Germany

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Johannes Kraus

University of Duisburg-Essen, Germany

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Jörg Schlötterer

Institute for AI in Medicine | Cancer Research Center Cologne Essen (CCCE), Germany

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Kai Ueltzhöffer

EMBL Heidelberg | Cancer Research Center Heidelberg, Germany

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Keyvan Farahani

National Cancer Institute, National Institutes of Health, Rockville, MD, USA

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Klaus H. Maier-Hein

Cancer Research Center, Germany

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Michael Kamp

Institute for AI in Medicine, Germany | Ruhr-University Bochum, Germany | Monash University, Australia

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Nicola Rieke

NVIDIA

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Nishant Ravikumar

School of Computing, University of Leeds, UK

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Robert Seifert

University Hospital Essen, Germany

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Seppo Virtanen

School of Computing, University of Leeds, UK

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Seyed-Ahmad Ahmadi

NVIDIA

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Shadi Albarqouni

University of Bonn | University Hospital Bonn | Helmholtz AI, Germany

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Victor Alves

Centro Algoritmi, University of Minho, Portugal

Organizing Team

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Sotirios Tsaftaris

Alan Turing Institute | ELLIS Fellow | University of Edinburgh,UK

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Vivek Sharma

Massachusetts Institute of Technology (MIT) | USA Harvard Medical School, Harvard University, USA

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Zhiming Cui

School of Biomedical Engineering, ShanghaiTech University, Shanghai

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Jan Egger

Institute for AI in Medicine, Germany

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Jana Fragemann

Institute for AI in Medicine, Germany

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Jens Kleesiek

Institute for AI in Medicine, Germany

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Jianning Li

Institute for AI in Medicine, Germany

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