Label-free fluorescence predictions from large-scale correlative light and electron microscopy data

Abstract

Volume electron microscopy (EM) has revolutionized the way in which biologists understand intraand intercellular systems. Due to the lack of biological specificity, however, interpretation of the data often requires tedious expert analysis and annotation. For this reason fluorescence microscopy (FM) is often used in conjunction with EM, complementing structural data with targeted biological labels. The downside, however is that sample preparation protocols are often laborious, time-consuming, and potentially damaging to the sample. Correlating these multi-modal datasets presents another challenge, which is compounded when registering across large spatial extents and then again for 3D.