EMCFsys

Electron microscope cell images foundation dataset with more than 4 million data.EMCF Dataset, the first large-scale, multi-domain foundation dataset specifically designed for deeplearning model pretraining. Its raw data were aggregated from two primary channels: millions images acquired in our laboratory and a vast collection of 2D and 3D images compiled from 6,825 public repositories, studies, and publications. Recognizing the inherent heterogeneity in magnification, resolution, and quality across these sources, we implemented a systematic curation pipeline to filter, clean, and standardize the data. This process yielded the final EMCF Dataset, comprising 4,002,802 high-quality electron micrographs. The dataset is characterized by its immense diversity, spanning 14 distinct EM technologies, including Transmission (TEM), Scanning (SEM), Focused Ion Beam SEM (FIB-SEM), and cryo-Electron Tomography (cryo-ET) and so on (Fig. 1c). Biologically, it covers six major kingdoms: Animalia, Plantae, Fungi, Protista, Bacteria, and Viruses.