DeepETPicker A deep learning based open-source software with a friendly user interface to pick 3D particles rapidly and accurately from cryo-electron tomograms

A deep learning based open-source software with a friendly user interface to pick 3D particles rapidly and accurately from cryo-electron tomograms. With the advantages of weak labels, lightweight architecture and GPU-accelerated pooling operations, the cost of annotations and the time of computational inference are significantly reduced while the accuracy is greatly improved by applying a Gaussian-type mask and using a customized architecture design.

DeepETPicker: Fast and accurate 3D particle picking for cryo-electron tomography using weakly supervised deep learning

Authors: Guole Liu, Tongxin Niu, Mengxuan Qiu, Yun Zhu, Fei Sun, and Ge Yang

Note: DeepETPicker is a Pytorch implementation.