Detecting Thalamic Abnormalities in Autism Using Cylinder Conformal Mapping

A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this paper, we applied advanced computational techniques to extract 3D surface models of the thalamus and subsequently analyze highly localized shape variations in a homogeneous group of autism children. In particular, a new conformal parameterization for high genus surfaces is applied in our shape analysis work, which maps the surfaces onto a cylinder domain. Surface matching among different individual meshes is achieved by re-triangulating each mesh according to the template. Children with autism and their controls are compared, and statistical significant abnormalities in thalamus of autism are detected.

[1]  Jing Hua,et al.  Brain Structure Segmentation from MRI by Geometric Surface Flow , 2006, Int. J. Biomed. Imaging.

[2]  David I. Perrett,et al.  A voxel-based investigation of brain structure in male adolescents with autistic spectrum disorder , 2004, NeuroImage.

[3]  Jason Adams,et al.  Brief Report: Abnormal Association Between the Thalamus and Brain Size in Asperger’s Disorder , 2008, Journal of autism and developmental disorders.

[4]  Shin Yoshizawa,et al.  Polygonal Curve Evolutions for Planar Shape Modeling and Analysis , 1999, Int. J. Shape Model..

[5]  P. Sahota,et al.  Essential versus complex autism: Definition of fundamental prognostic subtypes , 2005, American journal of medical genetics. Part A.

[6]  S. Yau,et al.  Global conformal surface parameterization , 2003 .

[7]  Qing He,et al.  Statistical Shape Analysis of the Corpus Callosum in Subtypes of Autism , 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

[8]  Hong Qin,et al.  Interactive shape modeling using Lagrangian surface flow , 2005, The Visual Computer.

[9]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[10]  O Musse,et al.  Three-dimensional segmentation of anatomical structures in MR images on large data bases. , 2001, Magnetic resonance imaging.

[11]  Martin Styner,et al.  Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM. , 2006, The insight journal.

[12]  Jason Adams,et al.  Abnormal brain size effect on the thalamus in autism , 2006, Psychiatry Research: Neuroimaging.

[13]  Ami Klin,et al.  Reduced thalamic volume in high-functioning individuals with autism , 2003, Biological Psychiatry.

[14]  Dimitris N. Metaxas,et al.  A hybrid framework for 3D medical image segmentation , 2005, Medical Image Anal..

[15]  T. Chan,et al.  Genus zero surface conformal mapping and its application to brain surface mapping. , 2004, IEEE transactions on medical imaging.