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Automated phenotyping is essential for the creation of large, highly standardized datasets from anatomical imaging data. Such datasets can support large‐scale studies of complex traits or clinical studies related to precision medicine or clinical trials. We have developed a method that generates three‐dimensional landmark data that meet the requirements of standard geometric morphometric analyses. The method is robust and can be implemented without high‐performance computing resources. We validated the method using both direct comparison to manual landmarking on the same individuals and also analyses of the variation patterns and outlier patterns in a large dataset of automated and manual landmark data. Direct comparison of manual and automated landmarks reveals that automated landmark data are less variable, but more highly integrated and reproducible. Automated data produce covariation …