Sorry could not resist commenting on the typo. No insult intended.
If you look at Keras' output, there are various steps which lose pixels:
Max pooling on odd sizes will always lose one pixel. Conv2D using 3x3 kernels will also lose 2pixels, although I'm puzzled that it doesn't seem to happen in the downsampling steps.
Intuitively, padding the original images with enough border pixels to compensate for the pixel loss due to the various layers would be the simplest solution. At the moment I can't calculate how much it should be, but I suspect rounding up to a multiple of 4 should take care of the max pooling layers. For denoising, borders could be just copied from the outermost pixels, probably with some sort of low pass filtering to avoid artefacts.
