Hello
I want to implement the U-net with Pytorch but I have several questions.
The first question is: The input of U-net is a slice of the abdominal CT scan and The organs must be segmented at the output, should I set the number of U-net output classes to the number of organs?
every slice has a size like 1x512x512
I set U-net input size to one, and output size(number of classes) to number of organs. I mean, is it right?
Second question: how many dimensional should Grand truth be?  Suppose we have 10 classes(10 organs). Should I create a tensor, which, in every dimension, is one of the organs maintained by Grand truth(10x512x512)? Or do I create a tensor with one dimension and identify each organ with an independent value(1x512x512)?