Label Space: A Coupled Multi-shape Representation

Richly labeled images representing several sub-structures of an organ occur quite frequently in medical images. For example, a typical brain image can be labeled into grey matter, white matter or cerebrospinal fluid, each of which may be subdivided further. Many manipulations such as interpolation, transformation, smoothing, or registration need to be performed on these images before they can be used in further analysis. In this work, we present a novel multi-shape representation and compare it with the existing representations to demonstrate certain advantages of using the proposed scheme. Specifically, we propose label space, a representation that is both flexible and well suited for coupled multishape analysis. Under this framework, object labels are mapped to vertices of a regular simplex, e.g. the unit interval for two labels, a triangle for three labels, a tetrahedron for four labels, etc. This forms the basis of a convex linear structure with the property that all labels are equ...

• Type: Conference
• Year: 2008
• Where: MICCAI
• Authors: James G. Malcolm, Yogesh Rathi, Martha Elizabeth Shenton, Allen Tannenbaum
• Keywords: Label Space, Medical Imaging, MICCAI 2008, Object Labels, Principal Component Analysis