Hi all.

Iam trying to train a convolutional variational autoencoder (CVAE) on computed tomography (CT) IMAGES (176X224 px) . The training data is normalized between 0 and 1 and Iam using approximately the same model structure as in keras autoencoder tutorial.

https://keras.io/examples/variational_autoencoder/

I only changed the depth and the size of the latent space to 128.

For the loss function I use Mse and KL, with a weight annealing for the KL part.

When I train the network it seems like it is learning something, but if I try to reconstruct images after training, the output images are just noisy.

I have no clue what it is Iam doing wrong.

Any advice would be really great.

Cheers,

M