We propose a new network structural similarity metric-based clustering protocol NCEM for clustering the noisy cryo-EM images. We first construct an image complex network for all the cryo-EM single particle images, where each image is represented as a node in the network. Then the similarity between two images is refined from network structural geometry. By extending the similarity measurement from two independent images to their corresponding neighbored sets in the network, this new NCEM has typical advantages over direct measurement of two images for its noise resistance by using the structural information of the network. This study is published in Yin et.al, Journal of Chemical Information and Modeling, 2019.