Abstract: The present disclosure provides a medical hyperspectral image (MHSI) classification method based on a fast fully convolutional network (FCN), and relates to the technical field of MHSIs. The MHSI classification method includes: preprocessing and sampling an MHSI to obtain a training sample set; inputting the training sample set into an encoder-decoder-based FCN to train the MHSI; and inputting a to-be-classified pixel of the MHSI into a trained encoder-decoder-based FCN to obtain a classification result. The present disclosure provides the MHSI classification method based on a fast FCN. In order to resolve problems of low efficiency and insufficient performance of an existing MHSI classification method, the present disclosure designs a classification method based on the fast FCN, which avoids redundant computation in an overlapping region between image patches, greatly improving an inference speed.