Automation of the full cycle of cryomicroscopic image processing: from collection to analysis

The article discusses the process of automating the full cycle of cryo-microscopic image processing using modern cloud technologies, annotation tools, artificial intelligence, and integration with platforms for scientific analytics. It describes a pipeline that includes stages such as data collection, storage using the MinIO cloud storage, image annotation with CVAT, the application of artificial intelligence models for inference, and result visualization. Special attention is given to the integration with Jupyter for scientific analysis and Docker to ensure scalability and reproducibility of the entire process. The advantages of automation are highlighted, providing convenience, scalability, reliability, and the ability to reuse results in scientific research, significantly enhancing the efficiency and accuracy of cryo-microscopic image analysis..