Brain surface conformal mapping research has been successful and this motivates our more general investigation of 3D volumetric brain harmonic mapping. By transforming the full 3D brain volume to a solid sphere, our goal is to investigate how features map into this canonical 3D coordinate system in the same way as 2D conformal flattening has helped in analyzing cortical surface geometry. Nonlinear mapping of two brain volumes to a sphere may also assist with the subsequent nonlinear registration of one brain volume to another. We suggest that 3D harmonic mapping of brain volumes to a solid sphere can provide a canonical coordinate system for feature identification and segmentation, as well as anatomical normalization. We developed two different techniques to tackle the volume mapping problem. The first finds a 3D harmonic map from a volumetric brain image to a 3D solid sphere and the second uses a sphere carving algorithm to compute a simplicial decomposition of the volume which is ad...
Yalin Wang, Xianfeng Gu, Tony F. Chan, Paul M. Tho