The shape of anatomic objects often depends in complex ways on the shapes and locations of neighboring objects. Shape parameter networks provide an approach for representing shape dependencies and producing multi-object models that share consistent boundary definitions. This paper provides an overview of the modeling framework provided by shape parameter networks, and demonstrates their use through the development of a detailed multi-object eye model. The eye model presented contains analytically defined shape equations that produce models matching user-specified physical measurements such as cornea width, cornea thickness, anterior chamber angle, and eye axial length.