MLOps Approach for Automatic Segmentation of Biomedical Images

When using artificial intelligence systems for processing medical images, a large amount of software libraries, data and cloud computing is required. Implementing deep learning elements in CAD is a complex process and applying DevOps can help speed up this process. The implementation of DevOps approaches in the field of machine learning differs from the operations with standard programs; therefore the development of MLOps approaches to the implementation of deep learning elements for the analysis of biomedical images is an actual task. The developed pipeline allows scientists and specialists to use the findings in this article to launch projects based on machine learning and focus on model development rather than the process of setting up the environment. This paper provides examples of improved MLOps pipelines that can be used for solving problems of automatic image segmentation and evaluating the quantitative characteristics of microobjects.