New Validation Technique for Cortical Data Smoothing (2009)
Over the years, various diffusion based cortical surface data smoothing techniques [1] [3] have been proposed but without any numerical validation. We present a novel validation
Cortical Surface Thickness as a Classifier: Boosting for Autism Classification ⋆ (2009)
Vikas Singh, Lopamudra Mukherjee, Moo K. Chung
Abstract. We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the highly...
Amygdala Surface Modeling with Weighted Spherical Harmonics (2009)
Moo K. Chung, M. Nacewicz, Shubing Wang, Kim M. Dalton, Seth Pollak, Richard J. Davidson
Abstract. Although there are numerous publications on amygdala volumetry, so far there has not been many studies on modeling local amygdala surface shape variations in a rigorous framework. This...
Detection of Local Cortical Asymmetry via Discriminant Power Analysis (2009)
Moo K. Chung, Daniel J. Kelley, Kim M. Dalton, Richard J. Davidson
We present a discriminant power analysis framework for localizing the abnormal cortical thickness asymmetry pattern in a clinical group. The proposed framework is based on the recently developed...
Amygdala Surface Modeling with Weighted Spherical Harmonics (2009)
Moo K. Chung, Brendon M. Nacewicz, Shubing Wang, Kim M. Dalton, Seth Pollak, Richardj. Davidson
Abstract. Although there are numerous publications on amygdala volumetry, so far there has not been many studies on modeling local amygdala surface shape variations in a rigorous framework. This...
Quantifying Cortical Surface Asymmetry via Logistic Discriminant Analysis (2009)
Moo K. Chung, Daniel J. Kelley, Kim M. Dalton, Richard J. Davidon
We present a computational framework for analyzing brain hemispheric asymmetry without any kind of image flipping. In almost all previous literature, to perform brain asymmetry analysis, it was...
Tensor-Based Cortical Surface Morphometry via Weighted Spherical Harmonic Representation (2009)
Moo K. Chung, Kim M. Dalton, Richard J. Davidson
Abstract—We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric...
Amygdala Surface Modeling with Weighted Spherical Harmonics (2009)
Moo K. Chung, M. Nacewicz, Shubing Wang, Kim M. Dalton, Seth Pollak, Richard J. Davidson
Abstract. Although there are many publications on amygdala volumetry, so far there has been no study on modeling local amygdala surface shape variations in a rigorous framework. This paper present a...
1 Department of Statistics, (2009)
Moo K. Chung, Mariana Lazar, Andrew L. Alex, Yuefeng Lu, Richard Davidson
We present a novel approach of obtaining white fiber anatomical connection probability in diffusion tensor imaging (DTI) via anisotropic Gaussian kernel smoothing. Our approach is compatible to other...
Large-scale modeling of parametric surfaces using spherical harmonics (2009)
We present an approach for large-scale modeling of parametric surfaces using spherical harmonics (SHs). A standard least square fitting (LSF) method for SH expansion is not scalable and cannot...
Statistica Sinica 18(2008), ENCODING CORTICAL SURFACE BY SPHERICAL HARMONICS (2009)
Moo K. Chung, Richard Hartley, Kim M. Dalton, Richard J. Davidson
Abstract: There is a lack of a unified statistical modeling framework for cerebral shape asymmetry analysis in the literature. Most previous approaches start with flipping the 3D magnetic resonance...
Detection of Local Cortical Asymmetry via Discriminant Power Analysis (2009)
Moo K. Chung, Daniel J. Kelley, Kim M. Dalton, Richard J. Davidson
We present a discriminant power analysis framework that can be used in localizing the abnormal cortical thickness asymmetry pattern in a clinical group compared with a control group. In our example,...
Amygdala Surface Modeling with Weighted Spherical Harmonics (2009)
Moo K. Chung, M. Nacewicz, Shubing Wang, Kim M. Dalton, Seth Pollak, Richard J. Davidson
Abstract. Although there are many publications on amygdala volumetry, so far there has been no study on modeling local amygdala surface shape variations in a rigorous framework. This paper present a...
Department of Psychology and Psychiatry, (2009)
Moo K. Chung, Kim M. Dalton, Richard J. Davidson
We present a new framework for cortical asymmetry analysis using the weighted spherical harmonic (SPHARM) representation (Chung et al., 2007). The weighted-SPHARM represents cortical surface...
A Unified Parametric Model (2009)
Moo K. Chung, Jee Eun Lee, Gary Park, Mariana Lazar, Nicholas T. Lange, ...
Abstract. We present a novel unified framework for explicitly parameterizing white fiber tracts. The coordinates of tracts are parameterized using a Fourier series expansion. For an arbitrary tract,...
on Mathematical Foundations of Computational Anatomy (2009)
Moo K. Chung, Anqi Qiu, M. Nacewicz, Seth Pollak, Richard J. Davidson
Abstract. One main obstacle in building a sophisticated parametric model along an arbitary anatomical manifold is the lack of an easily available orthonormal basis. Although there are at least two...
Li Shen, Andrew Saykin, Tara Mchugh, John West, Laura Rabin, Heather Wishart, ...
A computational framework is presented for morphometric analysis of 3D surfaces that aims to localize regionally specific shape changes between groups of 3D objects. This framework integrates a set...
New Validation Technique for Cortical Data Smoothing (2008)
Over the years, various diffusion based cortical surface data smoothing techniques [1,2] have been proposed but without numerical validation. We present a novel validation technique that uses the...
Localized Cortical Surface Asymmetry Analysis (2008)
Moo K. Chung, Kim Dalton, Richard J. Davidon
We present a computational framework for analyzing brain hemispheric asymmetry without any kind of image flipping. In order to perform brain asymmetry analysis, it is necessary to flip 3D magnetic...
Probabilistic Connectivity Using Kullback-Leibler Distance (2008)
Jee Eun Lee, Moo K. Chung, David Hsu, Andrew L. Alex
White matter tractography (WMT) is a promising method for characterizing the white matter pathways that connect brain regions. Probabilistic WMT is one approach to describe the white matter...
via Weighted Spherical Harmonic Representation (2008)
Moo K. Chung, Kim Dalton, Richard J. Davidson
Abstract: We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric...
Moo K Chung, Dalton M Kim, Steven Robbins, Alan C Evans, Richard J Davidson
We correlated face recognition task scores to cortical thickness measurements in a group of autistic subjects. Many previous autism anatomical studies neglect to account for age effect and the...
Encoding Cortical Surface by Spherical Harmonics (2008)
Moo K. Chung, Richard Hartley, Kim Dalton, Richard J. Davidson
Abstract: There is a lack of unified statistical modeling framework for cerebral shape asymmetry analysis in literature. Most previous approaches start with flip-ping the 3D magnetic resonance images...
Gaussian kernel smoothing has been widely used in 3D medical images as a way to increase signal-to-noise ratio and coloring dependent noise structure for random field theory, in part, due to its...
Moo K. Chung, Kim M. Dalton, Richard J. Davidson
Abstract — We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric...
Unified Cortical Asymmetry Analysis in Autism via Weighted-SPHARM (2008)
Moo K. Chung, Kim M. Dalton, Richard J. Davidson
We present a new framework for cortical asymmetry analysis using the weighted spherical harmonic (SPHARM) representation (Chung et al., 2007). The weighted-SPHARM represents cortical surface...
Automated Diagnosis of Autism Using Fourier Series Expansion of Corpus Callosum Boundary (2008)
Shubing Wang, Moo K. Chung, Kim M. Dalton, Andrew L. Alex, Richard J. Davidson
Multi-scale Voxel-based Morphometry via Weighted Spherical Harmonic Representation (2008)
Moo K. Chung, Li Shen, Kim M. Dalton, Richard J. Davidson
Abstract. Although the voxel-based morphometry (VBM) has been widely used in quantifying the amount of gray matter of the human brain, the optimal amount of registration that should be used in VBM...
Keith J. Worsley, Steve Robbins, Tomas Paus, Jonathan Taylor, Jay N. Giedd, Judith L. Rapoport, ...
We present a unified statistical approach to deformation-based morphometry applied to the cortical surface. The cerebral cortex has the topology of a 2D highly convoluted sheet. As the brain develops...
Moo K. Chung, Keith J. Worsley, D Steve Robbins, D Jonathan Taylor, Jay N. Giedd, ...
Deformation-based surface morphometry applied to gray
Abstract Less White Matter Concentration in Autism: (2007)
Moo K. Chung, Kim M. Dalton, Andrew L. Alex, Richard J. Davidson
Autism is a neurodevelopmental disorder affecting behavioral and social cognition but there is lit-tle understanding about the link between the functional deficit and its underlying neuroanatomy. We...
Abstract White Matter Density of Corpus Callosum in Autism: (2007)
Andrew L. Alex, Moo K. Chung, Moo K. Chung, Kim Dalton, Kim Dalton, ...
Autism is a neurodevelopmental disorder affecting behavioral and social cognition but there is little understanding about the link between the functional deficit and its underlying neuroanatomy. We...
On Expected Gaussian Random Determinants (2007)
The expectation of random determinants whose entries are real-valued, identically distributed, mean zero, correlated Gaussian random variables are examined using the Kronecker tensor products and...
Thomas J. Hoffmann, Moo K. Chung, Kim D. Dalton, Andrew L. Alex, Grace Wahba, Richard J. Davidson
Autism is a neurodevelopmental disorder with abnormal corpus callosum (CC) size [1]. Most previous studies used the area of predefined Witelson partition
Encoding neuroanatomical information using weighted spherical harmonic representation (2007)
Moo K. Chung, Kim M. Dalton, Richard J. Davidson
Cortical surfaces can be modeled using the recently developed weighed spherical harmonic (SPHARM) representation. The weighted-SPHARM representation incorporates data smoothing, parametrization and...
Of Gray Matter, Moo K. Chung, Kim M. Dalton, Li Shen, Alan C. Evans, Richard J. Davidson
representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination...
Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huang, James Ford, Fillia Makedon, ...
We study the connection between genotype and imaging phenotype in order to detect possible genetic risk factors in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We focus on...
Magnetic resonance image segmentation with thin plate spline thresholding (2006)
Xianhong Xie, Moo K. Chung, Grace Wahba
There are many ways to segment magnetic resonance image (MRI). Among them the SPM method, the neural network based method [1], and the level set method are well known. We
Evaluation of anisotropic filters for diffusion tensor imaging (2006)
Jee Eun Lee, Moo K. Chung, Andrew L. Alex
Diffusion tensor imaging (DTI) measures, such as fractional anisotropy (FA), and trace are very sensitive to noise contained in the acquired diffusion weighted images. Typical isotropic smoothing...
Multi-scale Voxel-based Morphometry via Weighted Spherical Harmonic Representation (2006)
Moo K. Chung, Li Shen, Kim M. Dalton, Richard J. Davidson, Moo K. Chung, Li Shen, ...
Abstract. Although the voxel-based morphometry (VBM) has been widely used in quantifying the amount of gray matter of the human brain, the optimal amount of registration that should be used in VBM...
Tensor-based cortical morphometry via weighted spherical harmonic representation (2006)
Moo K. Chung, Steve Robbins, Kim M. Dalton, Shubing Wang, Alan C. Evans, Richard J. Davidson
We present a new tensor-based morphometric framework that quantifies cortical shape variations using the local area element. The local area element is obtained from the Riemannian metric tensors,...
Unified Cortical Surface Morphometry and Its Application to Quantifying Amount of Gray Matter (2006)
Moo K. Chung, Moo K. Chung, Kim M. Dalton, Li Shen, Alan C. Evans, Richard J. Davidson
In quantifying the amount of gray matter in a population, voxelbased morphometry (VBM) and cortical thickness analysis are the two most widely used techniques. There are still many unanswered...
Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huang, James Ford, Fillia Makedon, ...
We study the connection between genotype and imaging phenotype in order to detect possible genetic risk factors in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We focus on...
Weighted spherical harmonic representation and its application to cortical analysis (2006)
Steven M. Robbins, Moo K. Chung, Moo K. Chung, Li Shen, Li Shen, Kim M. Dalton, ...
Abstract. We present a novel weighted spherical harmonic (SPHARM) representation of cortical surfaces and its application to a cortical thickness analysis in autism. The weighted-SPHARM is a...
Heat kernel smoothing on unit sphere (2006)
In brain imaging, cortical data such as the cortical thickness, cortical surface curvatures and surface coordinates have been mapped to a unit sphere for the purpose of visualization, surface...
In brain imaging, cortical data such as cortical thickness, surface curvatures and surface coordinates have been mapped to a unit sphere for visualization, surface registration and data analysis.
Unified statistical approach to cortical thickness analysis (2005)
Moo K. Chung, Steve Robbins, Alan C. Evans
Abstract. This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of data...
Cortical thickness analysis in autism with heat kernel smoothing (2005)
Moo K. Chung, Steven M. Robbins, Andrew L. Alex
We present a novel data smoothing and analysis framework for cortical thickness data defined on the brain cortical manifold. Gaussian kernel smoothing, which weights neighboring observations...
Anisotropic Kernel Smoothing in Diffusion Tensor Imaging: Theoretical Framework (2005)
Moo K. Chung, Jee Eun Lee, Andrew L. Alexender, Moo K. Chung, Jee Eun Lee, Andrew L. Alexender
We present a theoretical framework for smoothing diffusion tensor images. We formulate smoothing data along the white fiber tracks as iterated anisotropic Gaussian kernel smoothing. The formulation...
Mapping Brain-Behavior Partial (2005)
Moo K. Chung, Kim M. Dalton, Daniel J. Kelley, Steven M, Alan C. Evans, Richard J. Davidson, ...
This paper presents a streamlined image analysis framework for correlating behavioral measures to anatomical measures on the cortex and detecting the regions of abnormal brain-behavior correlates. We...
Heat Kernel Smoothing on Human Cortex Extracted from Magnetic Resonance Images (2005)
Summary. Gaussian kernel smoothing has been widely used in 3D whole brain imaging analysis as a way to increase signal-to-noise ratio. Gaussian kernel is isotropic in Euclidian space. However, data...
of Closed Anatomical Curves (2005)
We present a streamlined mathematical framework for modeling and classifying closed curves from medical images. The method of gradient vector flow (GVF) snakes is used to extract object boundaries in...
Gauss-Weierstrass Kernel Smoothing on Unit Sphere (2005)
In brain imaging, cortical data such as the cortical thickness, cortical surface curvatures and surface coordinates have been mapped to a unit sphere for the purpose of visualization, surface...
Abstract Tensor-based Cortical Morphometry via Weighted Spherical Harmonic Representation (2005)
Moo K. Chung, Steve Robbins, Kim M. Dalton, Shubing Wang, Alan C. Evans, Richard J. Davidson, ...
We present a new tensor-based morphometric framework that quantifies cortical shape variations via the concept of local area element. The local area element is obtained from the Riemannian metric...
Moo K. Chung, Steve Robbins, Alan C. Evans
We present a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. Due to the convoluted non-Euclidean surface geometry, data smoothing and
Diffusion smoothing on brain surface via finite element method (2004)
Surface data such as the segmented cortical surface of the human brain plays an important role in medical imaging. To increase the signal-to-noise ratio for data residing on the brain surface, the...
Diffusion Smoothing on Brain Surface via Finite Element Method (2004)
Introduction In order to perform statistical analysis on the brain cortical surface, data are usually diffused to increase the signal-to-noise ratio and Gaussianness [1, 3]. Most of the diffusion...
2D Voxel-based Morphometry Shows Less White Matter Concentration in Autism (2004)
Moo K. Chung, Kim D. Dalton, Andrew L. Alexander, Richard J. Davidson
Introduction Autism is a neurodevelopmental disorder with the abnormal reduction in anterior, midbody and posterior part of the corpus callosum (CC) [2]. We applied 2D version of the voxel-based...
Heat Kernel Smoothing and Statistical Inference on Manifolds (2004)
In computational neuroanatomy, there is need for analyzing data collected on the cortical surface of the human brain. Gaussian kernel smoothing has been widely used in this area in conjunction with...
Quantitative Analysis of Diffusion Tensor Orientation:Theoretical Framework (2004)
Yu-chien Wu, Aaron S. Field, Moo K. Chung, Benham Badie, Andrew L. Alex
Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps...
Diffusion smoothing on brain surface via finite element method (2004)
Surface data such as the segmented cortical surface of the human brain plays an important role in medical imaging. To increase the signal-to-noise ratio for data residing on the brain surface, the...
Tensor-based brain surface modeling and analysis (2003)
Moo K. Chung, Keith J. Worsley, Steve Robbins, Alan C. Evans
We present a unified computational approach to tensorbased morphometry in detecting the brain surface shape difference between two clinical groups based on magnetic resonance images. Our approach is...
Moo K. Chung, Moo K. Chung, Mariana Lazar, Mariana Lazar, Andrew L. Alexender, Andrew L. Alexender, ...
We present a novel probabilistic approach of representing the connectivity of the brain white fiber in diffusion tensor imaging via anisotropic Gaussian kernel smoothing. Our approach is simpler than...
Statistical Morphometry in Neuroanatomy (2001)
The scientific aim of computational neuroanatomy using magnetic resonance imaging (MRI) is to quantify inter- and intra-subject morphological variabilities. A unified statistical frame-work for...
Shubing Wang, Moo K. Chung, Kim M. Dalton, Andrew L. Alex, Richard J. Davidson
We explored the possibility of developing an automatic diagnostic tool for detecting autism based on MRI measurements. Since the two previous structural imaging studies [1] [2] strongly suggested...