Towards Automated TEM for Virus Diagnostics: Segmentation of Grid Squares and Detection of Regions of Interest

When searching for viruses in an electron microscope the sample grid constitutes an enormous search area. Here, we present methods for automating the image acquisition process for an automatic virus diagnostic application. The methods constitute a multi resolution approach where we first identify the grid squares and rate individual grid squares based on content in a grid overview image and then detect regions of interest in higher resolution images of good grid squares. Our methods are designed to mimic the actions of a virus TEM expert manually navigating the microscope and they are also compared to the expert’s performance. Integrating the proposed methods with the microscope would reduce the search area by more than 99.99 % and it would also remove the need for an expert to perform the virus search by the microscope.