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Ying Lu

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6 papers

2 author rows

IROS Conference 2014 Conference Paper

On the convergence of fixed-point iteration in solving complementarity problems arising in robot locomotion and manipulation

Ying Lu
Jeffrey C. Trinkle

Model-based approaches to the planning or control of robot locomotion or manipulation requires the solution of complementarity problems that model intermittent contact. Fixed-point iteration is a method of computing fixed points of functions and there are several fixed-point theorems to guarantee the existence of fixed points. With the help of proximal point functions, the complementarity problems that arise in multibody dynamics can be rewritten in a form suitable for solution by a fixed-point iteration method. This fixed-point “prox method” has been popular over the last decades. However, the tuning of the iteration parameter r is difficult, because r affects the convergence of the fixed-point iteration method in ways not understood by current theoretical results. In this paper, we first investigate some factors that affect the choice of r, which further determines the convergence rate. Also we study the loss of accuracy caused by a commonly used relaxation parameter, which is known as “constraint force mixing”.

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YNIMG Journal 2008 Journal Article

Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing

SungWon Chung
Daniel Pelletier
Michael Sdika
Ying Lu
Jeffrey I. Berman
Roland G. Henry

Diffusion tensor MRI (DTI) has been widely used to investigate brain microstructural changes in pathological conditions as well as for normal development and aging. In particular, longitudinal changes are vital to the understanding of progression but these studies are typically designed for specific regions of interest. To analyze changes in these regions traditional statistical methods are often employed to elucidate group differences which are measured against the variability found in a control cohort. However, in some cases, rather than collecting multiple subjects into two groups, it is necessary and more informative to analyze the data for individual subjects. There is also a need for understanding changes in a single subject without prior information regarding the spatial distribution of the pathology, but no formal statistical framework exists for these voxel-wise analyses of DTI. In this study, we present PERVADE (permutation voxel-wise analysis of diffusion estimates), a whole brain analysis method for detecting localized FA changes between two separate points in time of any given subject, without any prior hypothesis about where changes might occur. Exploiting the nature of DTI that it is calculated from multiple diffusion-weighted images of each region, permutation testing, a non-parametric hypothesis testing technique, was modified for the analysis of serial DTI data and implemented for voxel-wise hypothesis tests of diffusion metric changes, as well as for suprathreshold cluster analysis to correct for multiple comparisons. We describe PERVADE in detail and present results from Monte Carlo simulation supporting the validity of the technique as well as illustrative examples from a healthy subject and patients in the early stages of multiple sclerosis.

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YNIMG Journal 2006 Journal Article

Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters

SungWon Chung
Ying Lu
Roland G. Henry

Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. In this paper, two new approaches are introduced called residual bootstrap and repetition bootknife. We show that repetition bootknife corrects for the large bias present in the repetition bootstrap method and, therefore, better estimates the standard errors. Like wild bootstrap, residual bootstrap is applicable to single acquisition scheme, and both are based on regression residuals (called model-based resampling). Residual bootstrap is based on the assumption that non-constant variance of measured diffusion-attenuated signals can be modeled, which is actually the assumption behind the widely used weighted least squares solution of diffusion tensor. The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.

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YNIMG Journal 2005 Journal Article

Comparing microstructural and macrostructural development of the cerebral cortex in premature newborns: Diffusion tensor imaging versus cortical gyration

Amy R. deIpolyi
Pratik Mukherjee
Kanwar Gill
Roland G. Henry
Savannah C. Partridge
Srivathsa Veeraraghavan
Hua Jin
Ying Lu

This study assessed microstructural development in four regions of the human cerebral cortex during preterm maturation using diffusion tensor imaging (DTI), compared to the macrostructural development of cortical gyration evaluated using three-dimensional volumetric T1-weighted MR imaging. Thirty-seven premature infants of estimated gestational age (EGA) ranging from 25 to 38 weeks were prospectively enrolled and imaged in an MR-compatible neonatal incubator with a high-sensitivity neonatal head coil. Cortical gyration was measured quantitatively as the ratio of gyral height to width on the volumetric MR images in four regions bilaterally (superior frontal, superior occipital, precentral, and postcentral gyri). Mean diffusivity (D av), fractional anisotropy (FA—the fraction of D av that is anisotropic), and the three DTI eigenvalues (components of diffusivity radial and tangential to the pial surface of cortex) were measured in the same cortical regions. Cortical gyration scores, FA, and radial diffusivity were all significantly correlated with EGA (P < 0. 0001). However, in multivariate analysis, no significant relationship (P > 0. 05) was found between DTI parameters and cortical gyration beyond their common association with estimated gestational age. Pre- and postcentral gyri had significantly lower anisotropy than the superior occipital and superior frontal gyri (P < 0. 05), indicating that DTI is sensitive to regional heterogeneity in cortical development. Maturational changes in the DTI eigenvalues of cortical gray matter were found to differ from those that have previously been described in developing white matter, with a significant age-related decline in the radial diffusivity (P < 0. 0001) but not in the tangential diffusivities (P > 0. 05).

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YNIMG Journal 2004 Journal Article

Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns

Savannah C Partridge
Pratik Mukherjee
Roland G Henry
Steven P Miller
Jeffrey I Berman
Hua Jin
Ying Lu
Orit A Glenn

Magnetic resonance diffusion tensor imaging (DTI) enables the discrimination of white matter pathways before myelination is evident histologically or on conventional MRI. In this investigation, 14 premature neonates with no evidence of white matter abnormalities by conventional MRI were studied with DTI. A custom MR-compatible incubator with a novel high sensitivity neonatal head coil and improved acquisition and processing techniques were employed to increase image quality and spatial resolution. The technical improvements enabled tract-specific quantitative characterization of maturing white matter, including several association tracts and subcortical projection tracts not previously investigated in neonates by MR. Significant differences were identified between white matter pathways, with earlier maturing commissural tracts of the corpus callosum, and deep projection tracts of the cerebral peduncle and internal capsule exhibiting lower mean diffusivity (D av) and higher fractional anisotropy (FA) than later maturing subcortical projection and association pathways. Maturational changes in white matter tracts included reductions in D av and increases in FA with age due primarily to decreases in the two minor diffusion eigenvalues (λ 2 and λ 3). This work contributes to the understanding of normal white matter development in the preterm neonatal brain, an important step toward the use of DTI for the improved evaluation and treatment of white matter injury of prematurity.

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IS Journal 2003 Journal Article

Profile-based object matching for information integration

AnHai Doan
Ying Lu
Yoonkyong Lee
Jiawei Han

Traditional object-matching methods rely on similarities among shared attributes. Profile-based object matching builds on this approach but also correlates disjoint attributes to improve matching accuracy. To illustrate the PROM approach, we use two relational tables: one contains information about movies, the other about movie reviews.

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