Quantification and visualization of anatomical shape variability in different populations is essential for diagnosis and tracking progression of diseases. We present a new 3D medialbased shape representation method capable of analysis and visualization of 3D anatomy and demonstrate its ability to quantify and highlight shape variability in an intuitive manner. 3D shapes are represented via orientations and elongations of one or more medial sheets, along with thickness values encoding the distances to the shape surface. Two parameters traverse each medial sheet and are mapped to orientation, elongation, and thickness values; we call this map a medial patch. Shape variability is decomposed intuitively into bend, stretch, or bulge deformations, via operators acting on the components of the medial patch. In a simple manner, the location, extent, type, and amplitude of the deformation operators can be specified to capture local and global intuitive shape variability. We demonstrate the c...
Ghassan Hamarneh, Aaron D. Ward, Richard Frank