A significant set of challenges to the use of large, source ontologies in the medical domain include: automated translation, customization of source ontologies, and performance issues associated with the use of logical reasoning systems to interpret the meaning of a domain captured in a formal knowledge representation. SNOMED-CT and FMA are two reference ontologies that cover much of the domain of clinical informatics and motivate a better means for re-use. In this paper, we present a method for segmenting and merging modules from these ontologies for a specific domain that preserve the meaning of the anatomy terms they have in common.