SASHIMI: Simulation and Synthesis in Medical Imaging Call for Papers

First Call for Papers: 
SASHIMI: Simulation and Synthesis in Medical Imaging
A MICCAI 2017 Workshop 
September 10, 2017, Quebec City, Candata

In conjunction with MICCAI 2017 ( )

Important Dates:
 * Submission due:
June 12, 2017 
 * Notification of acceptance:
July 13, 2017 
 * Workshop event:
September 10, 2017
Scope of the Workshop:
The MICCAI community has always been close to the idea of creating
simulated or synthetic data to understand, develop, assess, and
validate image analysis and reconstruction algorithms. From very basic
digital phantoms all the way up to very realistic in silico models of
medical imaging and physiology, our community has progressed
enormously in terms of the available techniques and their
applications. For instance, mechanistic models (imaging simulations)
emulating the geometrical and physical aspects of the acquisition
process have been used now for a long time. Advances on computational
anatomy and physiology have further enhanced the potential of such
simulation platforms by incorporating structural and functional
realism to the simulations that can now account for complex
spatio-temporal dynamics due to changes in anatomy, physiology,
disease progression, patient and organ motion, etc. just to name a
few. More recently, developments in machine learning together with the
growing availability of ever-larger scale databases have provided the
theoretical underpinning and the practical data access to develop
phenomelogical models (image synthesis) that learn models directly
from data associations across subjects, time, modalities, resolutions,
etc. These techniques may provide ways to address challenging tasks in
medical image analysis like cross-cohort normalization, image
imputation in the presence of missing or corrupted data, transfer of
knowledge across imaging modalities, views or domains. To this date,
however, these two main research avenues (simulation and synthesis)
remain pretty much independent efforts in spite of sharing common
challenges. This satellite workshop, building on the successful 2016
edition, continues to provide a state-of-the-art and integrative
perspective on simulation and synthesis in medical imaging for the
purpose of invigorating research and stimulating new ideas on how to
build theoretical links, practical synergies, and best practices
between these two research directions.

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

* Fundamental methods for image-based biophysical modeling and image

* Biophysical and data-driven models of disease progression or organ
development, organ motion and deformation, image formation and

* Segmentation/registration across or within modalities to aid the
learning of model parameters

* Imaging protocol harmonization approaches across imaging systems,
sites and time points

* Image synthesis for normalization and spatio-temporal intensity

* Cross modality (PET/MR, PET/CT, CT/MR, etc.) image synthesis

* Simulation and synthesis from large-scale databases

* Automated techniques for quality assessment of simulations and
synthetic images

* Image synthesis in high dimensional spaces (vectors, tensors,
spatio-temporal features, etc.)

* Handling uncertainty and incomplete data via simulation and
synthesis techniques

* 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

* 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

Invited Speaker:
Prof. Hugo Larochelle, Google Brain & University of Sherbrooke, Canada.

Further Information and Submission Guidelines:
Workshop proceedings will be published as a Lecture Notes in Computer
Science volume (Springer).  Additional and up to date information
about the workshop, author instructions, submission guidelines, and
our invited speaker are available at:

Workshop Organization:
Workshop Chairs:
* Sotirios A Tsaftaris, University of Edinburgh, UK
* Ali Gooya, University of Sheffield, UK
* Alejandro F Frangi, University of Sheffield, UK
* Jerry L Prince, Johns Hopkins University, USA

Email to contact the organizers:

Program Committee:
Martino Alessandrini, University of Bologna, Italy
Daniel Alexander, University of College London, UK
Leandro Beltrachini, University of Sheffield, UK
M. Jorge Cardoso, University of College London, UK
Tim Cootes, University of Manchester, UK
Jan D'Hooge, KU Leuven, Belgium
Christos Davatzikos, University of Pennsylvania, USA
Marleen de Brujine, Erasmus University Medical Center, The Netherlands
Mathieu De Craene, Philips Research, France
Herve Delingette, Inria Sophia Antipolis, France
Dimitrios Fotiadis, University of Ioannina, Greece
Ali Gooya, University of Sheffield, UK
Daniel Herzka, John Hopkins University, USA
Ender Konukoglu, Martinos Center for Biomedical Imaging, USA
Sebastian Kozerke, Institute for Biomedical Engineering, ETH Zurich, Switzerland
Hervé Liebgott, CREATIS, France
David Liu, Siemens Medical Solutions, USA
Nassir Navab, TU Munich, Germany
Hien V Nguyen, Siemens Corporate Research, USA
Xenios Papademetris, Yale University, USA
Dzung L Pham, National Institutes of Health, USA
Adityo Prakosa, John Hopkins University, USA
Anqi Qiu, National University of Singapore, Singapore
Snehashis Roy, National Institutes of Health, USA
Daniel Rueckert, Imperial College, UK
Maxime Sermesant, Inria Sophia Antipolis, France
Ling Shao, Northumbria University, UK
Dinggang Shen, University of North Carolina, USA
François Varray, CREATIS, France
Devrim Unay, Izmir University of Economics, Turkey
Alistair Young, The University of Auckland, New Zealand
Kevin Zhou, Siemens Corporate Research, USA