An Arrpoach for Intersubject Analysis of 3D Brain Images Based on Conformal Geometry
Guangyu Zou, Jing Hua, Xianfeng Gu and Otto Muzik
International Conference on Image Processing ICIP 2006
Recent advances in imaging technologies, such as Magnetic
Resonance Imaging (MRI), Positron Emission Tomography (PET)
and Diffusion Tensor Imaging (DTI) have accelerated brain
research in many aspects. In order to better understand the synergy
of the many processes involved in normal brain function,
integrated modeling and analysis of MRI, PET, and DTI across
subjects is highly desirable. The current state-of-art computational
tools fall short in offering an analytic approach for intersubject
brain registration and analysis. In this paper we present an
approach which is based on landmark constrained conformal
parameterization of a brain surface from high-resolution structural
MRI data to a canonical spherical domain. This model allows
natural integration of information from co-registered PET as well
as DTI data and lays a foundation for the quantitative analysis of
the relationship among diverse datasets across subjects.
Consequently, the approach can be extended to provide a software
environment able to facilitate detection of abnormal functional
brain patterns in patients with neurological disorder.