Simulation and Synthesis in Medical Imaging

Страна: Греция

Город: Athens

Тезисы до: 10.06.2016

Даты: 21.10.16 — 21.10.16

Область наук: Технические; Медицинские;

Е-мейл Оргкомитета:

Организаторы: MICCAI Group


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 aims 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 synthesis
    Biophysical and data-driven models of disease progression or organ development, organ motion and deformation, image formation and acquisition
    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 correction
    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 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


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