Deep learning framework applied to optical diffraction tomography (ODT)

Optical diffraction tomography allows retrieving the 3D refractive index in a non-invasive and label-free manner. A sample is illuminated from various angles and the intensity of the diffracted light is recorded. The light wave can be calculated layer after layer and the inverse problem is usually solved using a gradient descent based algorithm. Here we propose a solution to solve the inverse problem using a neural network where the weights of each layer are the unknown refractive index of the object. Importantly, the matrix product between each layers is replaced by the physics of light propagation.