2017 Winter Project Week/OCM-MRI

From NAMIC Wiki
Revision as of 15:41, 13 January 2017 by Frank (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search
Home < 2017 Winter Project Week < OCM-MRI

Key Investigators

  • Frank Preiswerk, Brigham and Women's Hospital, Harvard Medical School
  • Yaofei Wang (Vivian), Tianjin University, Beijing, China

Project Description

Objective Approach and Plan Progress and Next Steps
  • To investigate the use of Deep Learning for the generation of synthetic respiratory MR images.
  • Look into different software frameworks, choose one
  • Investigate generative deep neural network techniques
  • Produce preliminary results on hybrid US+MRI data
  • Discussions
  • Installation of and finding our way around Keras and TensorFlow
  • Network candidates: CNN with logistic regression output, Generative Adversarial Networks (GAN), Variational Autoencoders
  • In particular, Variational Autoencoders are able to model conditional distributions as required here

Background and References