I’ve built a VAE network last week and trained it with Head images with and without motion artifact in patch size 40, 40, this is the architecture of the VAE network. The default padding is same, kernel sizes are all 3x3 and activation function is LeakyRelu.
Following pictures show the result of this architecture. It can predict the rough structures quite well and the motion artifact is reduced to some extent but some of the details are lost during the process as well. This is just a very basic network still needs to be optimized, but I think it is time to merge it into the master first.
I’ve built a VAE network last week and trained it with Head images with and without motion artifact in patch size
40, 40
, this is the architecture of the VAE network. The default padding issame
, kernel sizes are all3x3
and activation function isLeakyRelu
.Following pictures show the result of this architecture. It can predict the rough structures quite well and the motion artifact is reduced to some extent but some of the details are lost during the process as well. This is just a very basic network still needs to be optimized, but I think it is time to merge it into the master first.