  We describe a method for imaging 3D objects in a tomographic configuration
implemented by training an artificial neural network to reproduce the complex
amplitude of the experimentally measured scattered light. The network is
designed such that the voxel values of the refractive index of the 3D object
are the variables that are adapted during the training process. We demonstrate
the method experimentally by forming images of the 3D refractive index
distribution of cells.
