[2020] selected as a recipient of 2019 IEEE Signal Processing Society (SPS) BEST PAPER Award

Kyong Hwan Jin, Michael T. McCann, Emmanuel Froustey, and Michael Unser, "Deep Convolutional Neural Network for Inverse Problems in Imaging"

IEEE Transactions on Image Processing, Volume 26, No. 9, September 2017

K. H. Jin, H. Gupta, J. Yerly, M. Stuber, and M. Unser, "Time-Dependent Deep Image Prior for Dynamic MRI," arXiv
Summary : Unsupervised learning for reconstruction of dynamic MRI using generative network 

K. H. Jin, M. Unser, K. M. Yi, "Self-Supervised Deep Active Accelerated MRI," arXiv
Summary : Simultaneous learning of reconstructor and smart sampler with MCTS and policy network 

3D ConvNet classifier for Alzheimer is now published.
H. Choi and K. H. Jin, "Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging,"  Behavioural Brain Research, vol 344, (2018), pp 103-109
This work was also featured by MIT technology review (Apr. 28.2017) link

K. H. Jin, M.T. McCann, E. Froustey, M. Unser , "Deep Convolutional Neural Network for Inverse Problems in Imaging," IEEE Transactions on Image Processing, 26.9 (2017): 4509-4522. 
[The most frequently accessed document in IEEE TIP 2017.10~12, 2018.01]
Code (matlab, tensorflow) is open [github]


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