Topic: microscopy-like image stacks

Automatic methods for dendrite and dendritic spine segmentation are important for high-throughput neuroanatomical datasets. Assessing their performance compared to human annotators and ideally the real underlying neuroanatomy is crucial to determine overall reliability of those methods. However, most datasources, for example in two-photon microscopy, do not even allow identifying dendritic spines as an ultimate ground truth because of optical resolution limits. Here, we introduce synthetic microscopy to generate neuroanatomy stacks using a combination of random walk dendritic growth and random