I'm wondering if they are some state-of-art algorithms to apply the convolutional neural network approach to 3D pictures, eg. input is no longer a grid of pixels, but voxels. My objective is to extract automatically features from 3D pictures and, cherry on the cake, perform supervised learning using 3D pictures as input data. Maybe others approach exist to extract features, but I would like to stay in the scope of machine learning approach (eg. don't want to use methods such as Fourier transform). Thanks in advance for your insights!