Fig. 1.

The principle of the deep learning MR connectome. The connection between brain areas is expressed by a network graph consisting of nodes and edges. The “network graph” can be converted to an adjacent matrix and calculated by a graph theory. The adjacent matrix is similar to the image data and it can be an input of convolution neural network (CNN) model. The deep learning of MR connectome outputs the probability map which estimates the probability of AD, DLB and non-AD/DLB with a triangular graph. AD, Alzheimer’s disease; DLB, dementia with Lewy bodies.