In order to accurately measure the size of nanoparticles, an automatic particle segmentation method based on U-Net convolutional neural network is proposed according to the nanoparticle images captured by the transmission electron microscopy. Combined with the Batch Normalization (BN) layer, it reduces the dependence of networks on initialization and thus speeds up training. The nanoparticle image is filtered by the semi-implicit partial differential equation to enhance the image edge information. The improved U-Net network is used to train the nanoparticle individual segmentation model and the segmentation result is obtained. The research results show that the proposed method can accurately segment the nanoparticles in the image, and the segmentation effect is especially obvious for the nanoparticles with edge blurs and uneven intensities.