Workshop Details
The workshop will be held at W20-307 on Sept 14th, 2014. The objective of the workshop is two-fold. First, it will introduce fundamental concepts in imaging genetics, including concepts in computational biology and medical imaging. Second, it will facilitate discussion of novel modeling methods and new clinical applications and datasets through oral presentations of accepted abstracts. The workshop program has more details.
Author Details
Each accepted submission will present a poster, as well as a 5-minute oral presentation, which should mainly act as a teaser for the poster. The main goal is to get the audience interested in your poster, to encourage discussion. Talks should not include too much detailed information, but rather present an overview of the poster. Poster dimensions are the same as at the main conference. The posters will be put up in Room 202 -- Sala de Puerto Rico, and the boards will be marked 'MICGen'.
Tutorials
Our tutorials will introduce the fundamentals of clinical and molecular genetics, imaging genetics, and statistical methods relevant to the medical imaging community.
Invited guest speakers include:
- Mark Daly, Massachusetts General Hospital, Harvard Medical School
- Manolis Kellis, EECS, Massachusetts Institute of Technology
- Li Shen, Radiology and Imaging Sciences, Indiana University School of Medicine
- Jordan Smoller, Center for Human Genetic Research, Massachusetts General Hospital
Methods and Applications
Imaging genetics studies can comprise of a wide variety of heterogeneous sources of information with complex relationships and very large dimensionality. As current methods do not capture these complex interactions, joint representations and models of imaging and genetics are becoming important, making MICGen an ideal workshop for presenting novel frameworks. Simultaneously, clinical applications drive the research directions for methods development, and we invite abstracts and researchers presenting novel applications and datasets.
Contributors, especially those who employ Machine Learning tools in their analyses, will be invited to submit an extended version of their abstract to a special issue for IEEE Journal of Biomedical and Health Informatics (previously IEEE Transactions on Information Technology in Biomedicine). This special issue will be published in association with the MLMI 2014 Workshop.
For details regarding submissions, please see the call for abstracts.