Interpolation: How to generate 3D objects from 2D cross-sections?
A neural network is not a good choice for this.  For this task, you can get a much better solution by analytically solving for the unknown radius of the sphere.  In particular, if the radius of the sphere is $s$, then a slice at height $z$ will have radius $r$, where these three variables satisfy the equation

$$(s-z)^2 + r^2 = s^2.$$

Re-arranging, we find

$$s = {z^2 + r^2 \over 2z}.$$

So, you can solve immediately for the radius of the sphere.  Once you know the radius of the sphere, you can predict the radius of other slices at any height of your choice, using the above equations a second time.



You could certainly train a neural network to interpolate, given enough training data.  For instance, the input to the neural network might be 6 images: the three slices "above" z, and the three "below", and the output is a bunch of slices interpolated between the one above z and the one below; where each image is a picture of the slice.  However I'm not sure how well this will work, and it will likely require a lot of training data to have any chance whatsoever of being useful, so you might do better to look for some other solution.