Front Cover: Automated segmentation of insect anatomy from micro-CT images using deep learning

Abstract

Micro-CT imaging has become readily accessible for morphological biology studies, generating data at overwhelming rates. To facilitate ecological discovery, micro-CT-produced 3D images of animals need efficient processing and analysis. However, segmentation of inner parts of scanned specimens can be very time-consuming. In this cover article ntls.20230010, Evropi Toulkeridou and colleagues develop a deep learning-based pipeline for accurate, fully automated segmentation of micro-CT images of insects, designed for ant brains but extendable to other insects. Further, their annotated dataset is among the first for micro-CT images of insects.