Biomedical subjects

Yanxi Liu

Publications and source records attributed to Yanxi Liu.

5 recordsLinked to original sources

PubMed2006

Ventricular volume and dementia progression in the Cardiovascular Health Study.

Elevated cerebral ventricular volume may be associated with dementia risk and progression. A fully-automated technique that agreed highly with radiological readings was used to estimate lateral ventricle volume on MR scans done at baseline in 1997-99 of 377 subjects in the Cardiovascular Health Study (CHS) from the Pittsburgh Center. 327 subjects were normal or diagnosed with mild cognitive impairment (MCI) at baseline and were evaluated 4 years later. Baseline ventricular volume was analyzed in multivariate models with age, gender, education level, presence and incidence of cerebral infarcts, and dementia category (normal, MCI, or dementia) at baseline and follow-up as fixed effects. Ventricular volume at baseline was significantly higher among subjects normal at baseline and demented 4 years later. Age, gender, education level, and dementia progression were significant factors affecting ventricular volume. Ventricular volume was higher in dementia compared to MCI, higher in MCI compared to controls, and higher in Possible-Alzheimer's-disease (AD) dementia compared to Probable-AD. Larger ventricles in healthy subjects may indicate susceptibility to, or progression of, dementia-related pathology.

Aged↗

PubMed2006

The role of structural facial asymmetry in asymmetry of peak facial expressions.

Asymmetric facial expression is generally attributed to asymmetry in movement, but structural asymmetry in the face may also affect asymmetry of expression. Asymmetry in posed expressions was measured using image-based approaches in digitised sequences of facial expression in 55 individuals, N=16 men, N=39 women. Structural asymmetry (at neutral expression) was higher in men than women and accounted for .54, .62, and .66 of the variance in asymmetry at peak expression for joy, anger, and disgust expressions, respectively. Movement asymmetry (measured by change in pixel values over time) was found, but was unrelated to peak asymmetry in joy or anger expressions over the whole face and in facial subregions relevant to the expression. Movement asymmetry was negatively related to peak asymmetry in disgust expressions. Sidedness of movement asymmetry (defined as the ratio of summed movement on the left to movement on the right) was consistent across emotions within individuals. Sidedness was found only for joy expressions, which had significantly more movement on the left. The significant role of structural asymmetry in asymmetry of emotion expression and the exploration of facial expression asymmetry have important implications for evolutionary interpretations of facial signalling and facial expressions in general.

Affect↗

PubMed2005

Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment.

This study assesses the performance of public-domain automated methodologies for MRI-based segmentation of the hippocampus in elderly subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural MR images of 54 age- and gender-matched healthy elderly individuals, subjects with probable AD, and subjects with MCI were collected at the University of Pittsburgh Alzheimer's Disease Research Center. Hippocampi in subject images were automatically segmented by using AIR, SPM, FLIRT, and the fully deformable method of Chen to align the images to the Harvard atlas, MNI atlas, and randomly selected, manually labeled subject images ("cohort atlases"). Mixed-effects statistical models analyzed the effects of side of the brain, disease state, registration method, choice of atlas, and manual tracing protocol on the spatial overlap between automated segmentations and expert manual segmentations. Registration methods that produced higher degrees of geometric deformation produced automated segmentations with higher agreement with manual segmentations. Side of the brain, presence of AD, choice of reference image, and manual tracing protocol were also significant factors contributing to automated segmentation performance. Fully automated techniques can be competitive with human raters on this difficult segmentation task, but a rigorous statistical analysis shows that a variety of methodological factors must be carefully considered to insure that automated methods perform well in practice. The use of fully deformable registration methods, cohort atlases, and user-defined manual tracings are recommended for highest performance in fully automated hippocampus segmentation.

Aged↗

PubMed2005

Online selection of discriminative tracking features.

This paper presents an online feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance. Our hypothesis is that the features that best discriminate between object and background are also best for tracking the object. Given a set of seed features, we compute log likelihood ratios of class conditional sample densities from object and background to form a new set of candidate features tailored to the local object/background discrimination task. The two-class variance ratio is used to rank these new features according to how well they separate sample distributions of object and background pixels. This feature evaluation mechanism is embedded in a mean-shift tracking system that adaptively selects the top-ranked discriminative features for tracking. Examples are presented that demonstrate how this method adapts to changing appearances of both tracked object and scene background. We note susceptibility of the variance ratio feature selection method to distraction by spatially correlated background clutter and develop an additional approach that seeks to minimize the likelihood of distraction.

Algorithms↗

PubMed2004

A computational model for periodic pattern perception based on frieze and wallpaper groups.

We present a computational model for periodic pattern perception based on the mathematical theory of crystallographic groups. In each N-dimensional Euclidean space, a finite number of symmetry groups can characterize the structures of an infinite variety of periodic patterns. In 2D space, there are seven frieze groups describing monochrome patterns that repeat along one direction and 17 wallpaper groups for patterns that repeat along two linearly independent directions to tile the plane. We develop a set of computer algorithms that "understand" a given periodic pattern by automatically finding its underlying lattice, identifying its symmetry group, and extracting its representative motifs. We also extend this computational model for near-periodic patterns using geometric AIC. Applications of such a computational model include pattern indexing, texture synthesis, image compression, and gait analysis.

Algorithms↗