 Bayesian model of computational anatomy

Bayesian models of computational anatomy are statistical frameworks used to analyze and interpret anatomical structures in medical imaging, leveraging Bayesian inference to account for variability and uncertainty in anatomical data. This approach is particularly useful in fields like neuroimaging, where individual anatomical structures may vary significantly among subjects. ### Key Concepts: 1. **Bayesian Inference**: At its core, Bayesian analysis involves updating the probability of a hypothesis as more evidence or data becomes available.