You could add a two-element (convolutional) softmax layer on the output to get 
a pair of class probabilities. Taking the argmax of that would give you the 
predicted class. I just use cross entropy on the two class unets and it seems 
to work fine. I think lasagna has some other options built in if you're using 
that. 

To do a convolutional softmax layer you'll need to write a custom softmax 
function that can handle the two spatial dimensions. It's a one liner though, 
easy to write from the equation given in the theano documentation. 

I assume the challenge is to identify the teeth?

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