Welcome to our tutorial page for MICCAI 2020
October 4th 7am-11.30am PDT / 16u-19.30u CET
This tutorial is focused on an introduction to machine learning approaches for data fusion of imaging and non-imaging data for clinical decision support organized on behalf of the AMIA biomedical imaging informatics working group.
- William Hsu - UCLA
- Arvind Rao - University of Michigan
- Olivier Gevaert - Stanford University
Vast amounts of biomedical data are now routinely available for patients, ranging from radiographic images to clinical and genomic data, spanning multiple biological scales. AI and machine learning are increasingly used to enable pattern discovery to link such data for improvements in patient diagnosis, prognosis and tailoring treatment response. Yet, few studies focus on how to link different types of imaging and non-imaging biomedical data in synergistic ways, and to develop data fusion approaches for clinical decision support. This tutorial will describe considerations, approaches, software toolkits, and open challenges related to multi-omics, multi-modal and multi-scale data fusion of imaging and non-imaging biomedical data in the context of clinical decision support.
Session 1: Introduction to data fusion of imaging and non-imaging data - 7am-8am PDT / 16-17u CET
- Olivier Gevaert - Stanford University - Introduction to data modalities and data fusion
- William Hsu - UCLA - Quantitative analysis of radiographic images in the context of non-imaging data :movie_camera:
- Arvind Rao - University of Michigan - Data fusion of multi-omics and imaging data :movie_camera:
- Live Panel discussion with speakers including Q&A at 8am PDT / 17u CET
Session 2: Examples of data fusion of imaging and non-imaging data - 8.40am-9.20am PDT / 17u40-18u20 CET
- Anahita Fathi Kazerooni - University of Pennsylvania - Quantitative analysis of MR images using radiogenomics :movie_camera:
- Mirabela Rusu - Stanford University - Integration of pathology and radiology imaging :movie_camera:
- Live Panel discussion with speakers & organizers including Q&A at 9.30am PDT / 18u30 CET
- Martin Vallières - Université de Sherbrooke - Medomics a software framework for integrating omics and imaging data :movie_camera:
- Andrey Fedorov - Harvard University - Introduction to the NCI Imaging Data Commons and it’s connection to other NCI data commons :movie_camera:
- Live Panel discussion with speakers & organizers including Q&A at 11am PDT / 19u CET
All times are approximate and will be updated 1 week before the tutorial date of October 4th.
:movie_camera: prerecorded presentations by speakers.