[7 . 22 . 2014] Please use LNCS templates for final abstracts: Word or Latex
[7 . 10 . 2014] Acceptance emails have been sent out.
[6 . 24 . 2014] The submission website has been closed. Thank you to all of the submitters!
[6 . 17 . 2014] We've extended the deadline to Friday, June 20th 11:59PM PDT
[6 . 03 . 2014] Registration is open.
Note that if you wish, you can register and pay for just the MICGen workshop.
[6 . 02 . 2014] Added program link and invited speakers. [5 . 27 . 2014] Submission Site Open [3 . 20 . 2014] Call for Extended Abstracts
[3 . 09 . 2014] Website Launched
MICGen: MICCAI Workshop on Imaging Genetics will be held on September 14th, 2014, in conjunction with the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference, and will take place at the Massachusetts Institute of Technology, Cambridge, MA, USA. It will bring together researchers and clinicians from various fields including medical genetics, computational biology and medical imaging, presenting a forum for both fundamental concepts as well as state-of-the-art methods and applications.
MICGen will include tutorial sessions introducing the fundamental concepts and challenges of imaging genetics, as well as oral presentations of accepted abstracts presenting novel methods or new applications. All researchers interested in imaging genetics, regardless of experience, are invited to attend.
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.
Imaging genetics studies the relationships between genetic variation and measurements from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses are successful for deciphering simple genetic traits, imaging genetics can aid in understanding the underlying complex genetic mechanisms of multifaceted phenotypes. Specifically, imaging-based biomarkers are used as an intermediate or alternative phenotype that provides a rich quantitative characterization of disease. As large imaging genetics datasets are becoming available, their analysis poses unprecedented methodological challenges. MICCAI offers an ideal and timely opportunity to bring together people with different expertise and shared interests in this rapidly evolving field.