SASHIMI 2020: Simulation and Synthesis in Medical Imaging


SASHIMI: Simulation and Synthesis in Medical Imaging

A MICCAI 2020 Virtual Workshop
October 4, 2020


In conjunction with MICCAI 2020 (

Call for papers

SASHIMI 2020 will be held virtually! The workshop will take place on October 4th and the proceedings will be published, as planned. The event will include a mix of pre-recorded talks, live Q/A, and live panel discussions. More details to come!

Important Dates:

Submission due:    June 30
Notification of acceptance:    July 21

Camera ready:    July 31
Workshop event:    October 4

Scope of the Workshop:

The MICCAI community needs data with known ground truth to develop, evaluate, and validate computerized image analytic tools, as well as to facilitate clinical training. Since synthetic data are ideally suited for this purpose, a full range of models underpinning image simulation and synthesis, also referred to as image translation, cross-modality synthesis, image completion, etc. have been developed over the years: (i) machine and deep learning methods based on generative models; (ii) simplified mathematical models to test segmentation, tracking, restoration, and registration algorithms; (iii) detailed mechanistic models (top–down), which incorporate priors on the geometry and physics of image acquisition and formation processes; and (iv) complex spatio-temporal computational models of anatomical variability, organ physiology, and morphological changes in tissues or disease progression.

The goal of SASHIMI is to bring together all those interested in such problems in order to engage in invigorating research, discuss current approaches, and stimulate new ideas and scientific directions in this field. The objectives are to (a) bring together experts on image synthesis to raise the state of the art; (b) hear from invited speakers outside of the MICCAI community, for example in the areas of transfer learning, generative adversarial networks, or variational autoencoders, to cross-fertilize these fields; and (c) identify challenges and opportunities for further research. We also want to identify the suitable approaches to evaluate the plausibility of synthetic data and to collect benchmark data that could help with the development of future algorithms.


Specific topics of interest include, but are not limited to, the following:

  • Fundamental methods for image-based biophysical modelling and image synthesis
  • Biophysical and data-driven models of disease progression, organ development, motion and deformation, image formation and acquisition
  • Virtual cell imaging
  • Segmentation/registration across or within modalities to aid model parameter learning
  • Imaging protocol harmonization approaches across imaging systems, sites and time points
  • Cross-modality image synthesis
  • Image synthesis for normalization and spatio-temporal intensity correction
  • Simulation and synthesis from large-scale databases
  • Machine and deep learning techniques in image simulation and synthesis
  • Handling uncertainty and incomplete data via simulation and synthesis techniques
  • Automated techniques for quality assessment of simulations and synthetic images
  • Evaluation and benchmarking of state-of-the-art approaches in simulation and synthesis
  • Novel ideas on evaluation metrics and methods in image-based simulation and image synthesis
  • Normative and annotated datasets for benchmarking and learning models
  • Applications of image synthesis/simulation in super resolution imaging and multi/cross-scale regression, registration, segmentation, denoising, fusion reconstruction and real-time simulation of biophysical properties

Further Information and Submission Guidelines:

The SASHIMI 2020 workshop will accept 10-page papers (LNCS-Springer format), similar to the MICCAI format. Accepted papers will be published in a Lecture Notes in Computer Science volume published by Springer.

Workshop Organization:

Organising Committee:

Ninon Burgos, CNRS - Paris Brain Institute, France

David Svoboda, Masaryk University, Czech Republic

Jelmer Wolterink, University of Twente, The Netherlands

Can Zhao, Nvidia, Johns Hopkins University, USA

Email to contact the organizers: This email address is being protected from spambots. You need JavaScript enabled to view it.

Program Committee:

Ninon Burgos, CNRS - Paris Brain Institute, France

Aaron Carass, John Hopkins University, USA

Blake Dewey, John Hopkins University, USA

Florien Dubost, Erasmus MC Rotterdam, NL

Hamid Fehri, University of Oxford, UK

Thomas Joyce, ETH Zurich, Switzerland

Martin Maška, Masaryk University, Czech Republic

Jack Noble, Vanderbilt University, USA

Dzung L Pham, National Institutes of Health, USA

Nishant Ravikumar, University of Leeds, UK

David Svoboda, Masaryk University, Czech Republic

Vladimír Ulman, Max Planck Institute of Molecular Cell Biology and Genetics, Germany

Devrim Unay, Izmir University of Economics, Turkey

François Varray, CREATIS, France

Jelmer Wolterink, University of Twente, NL

Can Zhao, Nvidia, Johns Hopkins University, USA

Ting Zhao, Janelia Research Campus, USA

Arezoo Zakeri, University of Leeds, UK

Can Zhao, Nvidia, Johns Hopkins University, USA

Ting Zhao, Janelia Research Campus, USA

Organization committee

Ninon Burgos
CNRS - Paris Brain Institute, France
David Svoboda
Masaryk University, Czech Republic
elmer Wolterink
University of Twente, The Netherlands
Can Zhao
Nvidia, Johns Hopkins University, USA