View source for 2017 Winter Project Week/OCM-MRI

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Image:PW-Winter2017.png|link=2017_Winter_Project_Week#Projects|[[2017_Winter_Project_Week#Projects|Projects List]]
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==Key Investigators==
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* Frank Preiswerk, Brigham and Women's Hospital, Harvard Medical School
* Yaofei Wang (Vivian), Tianjin University, Beijing, China

==Project Description==
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! style="text-align: left; width:27%" |   Objective
! style="text-align: left; width:27%" |   Approach and Plan
! style="text-align: left; width:27%" |   Progress and Next Steps
|- style="vertical-align:top;"
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* To investigate the use of Deep Learning for the generation of synthetic respiratory MR images.
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* Look into different software frameworks, choose one
* Investigate generative deep neural network techniques
* Produce preliminary results on hybrid US+MRI data
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* 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
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==Background and References==
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* http://link.springer.com/chapter/10.1007%2F978-3-319-24553-9_39#page-1
* http://onlinelibrary.wiley.com/doi/10.1002/mrm.26467/full