Anatomic Objects from Medical Images

Figural object models represent object shape in terms of a hierarchy of simple shapes, protrusions, and indentations that we call "figures". Each figure has an unbranching, coarsely sampled net of medial primitives which carr>.: width information. The figural hierarchy and its medial primitives thus define the boundary with a -tolerance proportional to the corresponding medial widths, and associate with eacl~ boundary location a normal vector representing the figural boundary at a scale proportional to the medial width. Such a model is efficiently and effectively deformable to match image information according to, and producing, probabilistic measures of object shape and measures of image match. This paper specifies the makeup of figural object models and describes methods for building models of anatomic objects.