Difference between revisions of "2017 Winter Project Week/OCM-MRI"
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<!-- Approach and Plan bullet points --> | <!-- Approach and Plan bullet points --> | ||
* Look into different software frameworks, choose one | * Look into different software frameworks, choose one | ||
− | * Investigate generative deep neural | + | * Investigate generative deep neural network techniques |
* Produce preliminary results on hybrid US+MRI data | * Produce preliminary results on hybrid US+MRI data | ||
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<!-- Progress and Next steps bullet points (fill out at the end of project week) --> | <!-- Progress and Next steps bullet points (fill out at the end of project week) --> | ||
− | * | + | * 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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Latest revision as of 15:41, 13 January 2017
Home < 2017 Winter Project Week < OCM-MRIKey Investigators
- Frank Preiswerk, Brigham and Women's Hospital, Harvard Medical School
- Yaofei Wang (Vivian), Tianjin University, Beijing, China
Project Description
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