  Imaging algorithms form powerful analysis tools for VLBI data analysis.
However, these tools cannot measure certain image features (e.g., ring
diameter) by their non-parametric nature. This is unfortunate since these image
features are often related to astrophysically relevant quantities such as black
hole mass. This paper details a new general image feature extraction technique
that applies to a wide variety of VLBI image reconstructions called variational
image domain analysis. Unlike previous tools, variational image domain analysis
can be applied to any image reconstruction regardless of its structure. To
demonstrate its flexibility, we analyze thousands of reconstructions from
previous EHT synthetic datasets and recover image features such as diameter,
orientation, and asymmetry. By measuring these features, VIDA can help extract
astrophysically relevant quantities such as the mass and orientation of M 87.
