Master of Science

thesisTraumatic brain injury (TBI) is a leading cause of death and disability in the U.S.A. In mild cases, common etiologies of TBI (i.e., hemorrhage or edema) are not readily apparent during medical examination. We propose that the pia-arachnoid complex (PAC) contributes to the brain's response in TBI. The PAC is the only layer of tissue between the brain and dura (a tough membrane tightly adhered to the skull), and acts as a mechanical tether between the brain and skull. If the fine structures of the PAC are damaged during TBI, they likely go undiagnosed due to their small size and difficulty to image. To better understand the mechanics of PAC injury, several experimental and computational studies were conducted. First, a novel application of optical coherence tomography (OCT) was utilized to acquire microscale images of the in-situ porcine PAC and measure the amount of arachnoid trabeculae (AT) present. Next, two parametric studies were conducted on a microscale model of the PAC which evaluated its sensitivity to variable substructure moduli and AT volume fraction (VF). Afterwards, the microscale PAC model was paired with a macroscale head model to determine the effect of a nonuniform AT VF on whole-head mechanics. Finally, an immature porcine model of mild TBI was used to investigate PAC damage following head rotation, and identify clinically relevant MRI biomarkers indicative of PAC damage. The OCT imaging of the PAC revealed high variability of VF within each head, but low variability between brain regions and between animals. The microscale parametric studies showed high sensitivity to changes in substructure moduli and VF. The macroscale model studies showed improvement of intracranial hemorrhage prediction when variable VF was introduced into the models. Clinically relevant biomarkers of PAC damage were not able to be confidently developed, but increased sample size and improved resolution may lead to innovative biomarkers for TBI. The work presented here addresses a significant lack of data on the PAC, and presents new insights into its anatomy and biomechanics. Many of the studies presented here are the first of their kind, opening up many new paths of TBI research opportunities

Population-based fitting of medial shape models with correspondence optimization

pre-printA crucial problem in statistical shape analysis is establishing the correspondence of shape features across a population. While many solutions are easy to express using boundary representations, this has been a considerable challenge for medial representations. This paper uses a new 3-D medial model that allows continuous interpolation of the medial manifold and provides a map back and forth between it and the boundary. A measure defined on the medial surface then allows one to write integrals over the boundary and the object interior in medial coordinates, enabling the expression of important object properties in an object-relative coordinate system.We use these integrals to optimize correspondence during model construction, reducing variability due to the model parameterization that could potentially mask true shape change effects. Discrimination and hypothesis testing of populations of shapes are expected to benefit, potentially resulting in improved significance of shape differences between populations even with a smaller sample size

Image pattern recognition supporting interactive analysis and graphical visualization

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis

Polychromatic polarization microscope : bringing colors to a colorless world

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 5 (2015): 17340, doi:10.1038/srep17340.Interference of two combined white light beams produces Newton colors if one of the beams is retarded relative to the other by from 400 nm to 2000 nm. In this case the corresponding interfering spectral components are added as two scalars at the beam combination. If the retardance is below 400 nm the two-beam interference produces grey shades only. The interference colors are widely used for analyzing birefringent samples in mineralogy. However, many of biological structures have retardance <100 nm. Therefore, cells and tissues under a regular polarization microscope are seen as grey image, which contrast disappears at certain orientations. Here we are proposing for the first time using vector interference of polarized light in which the full spectrum colors are created at retardance of several nanometers, with the hue determined by orientation of the birefringent structure. The previously colorless birefringent images of organelles, cells, and tissues become vividly colored. This approach can open up new possibilities for the study of biological specimens with weak birefringent structures, diagnosing various diseases, imaging low birefringent crystals, and creating new methods for controlling colors of the light beam.This publication was made possible by Grant Number R01-GM101701 from the National Institute of General Medical Sciences, National Institutes of Health

Robust and flexible multi-scale medial axis computation

The principle of the multi-scale medial axis (MMA) is important in that any object is detected at a blurring scale proportional to the size of the object. Thus it provides a sound balance between noise removal and preserving detail. The robustness of the MMA has been reflected in many existing applications in object segmentation, recognition, description and registration. This thesis aims to improve the computational aspects of the MMA. The MMA is obtained by computing ridges in a “medialness” scale-space derived from an image. In computing the medialness scale-space, we propose an edge-free medialness algorithm, the Concordance-based Medial Axis Transform (CMAT). It not only depends on the symmetry of the positions of boundaries, but also is related to the symmetry of the intensity contrasts at boundaries. Therefore it excludes spurious MMA branches arising from isolated boundaries. In addition, the localisation accuracy for the position and width of an object, as well as the robustness under noisy conditions, is preserved in the CMAT. In computing ridges in the medialness space, we propose the sliding window algorithm for extracting locally optimal scale ridges. It is simple and efficient in that it can readily separate the scale dimension from the search space but avoids the difficult task of constructing surfaces of connected maxima. It can extract a complete set of MMA for interfering objects in scale-space, e.g. embedded or adjacent objects. These algorithms are evaluated using a quantitative study of their performance for 1-D signals and qualitative testing on 2-D images

Improved modelling of the human cerebral vasculature

Ph.DDOCTOR OF PHILOSOPH

Edge detection and ridge detection with automatic scale selection

When extracting features from image data, the type of information that can be extracted may be strongly dependent on the scales at which the feature detectors are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of scale levels when detecting one-dimensional features, such as edges and ridges. Anovel concept of a scale-space edge is introduced, defined as a connected set of points in scale-space at which: (i) the gradient magnitude assumes a local maximum in the gradient direction, and (ii) a normalized measure of the strength of the edge response is locally maximal over scales. An important property of this definition is that it allows the scale levels to vary along the edge. Two specific measures of edge strength are analysed in detail. It is shown that by expressing these in terms of &amp;gamma;-normalized derivatives, an immediate consequence of this definition is that fine scales are selected for sharp edges (so as to reduce the shape distortions due to scale-space smoothing), whereas coarse scales are selected for diffuse edges, such that an edge model constitutes a valid abstraction of the intensity profile across the edge. With slight modifications, this idea can be used for formulating a ridge detector with automatic scale selection, having the characteristic property that the selected scales on a scale-space ridge instead reflect the width of the ridge

The thalamocortical symphony:How thalamus and cortex play together in schizophrenia and plasticity

The work presented in this thesis aimed at investigating the function and mechanism of corticothalamic-thalamocortical network in schizophrenia and experience-dependent plasticity, further discussed their possible connection.In Chapter 2, we examined the effects of low-dose ketamine on the corticothalamic circuit (CTC) system. Our findings reveal that ketamine induces abnormal spindle activity and gamma oscillations in the CTC system. Notably, ketamine also leads to a transition in thalamic neurons from burst-firing to tonic action potential mode, which may underlie deficits in spindle oscillations. Chapter 3 addresses sensory perception deficits in schizophrenia, emphasizing disruptions in beta and gamma frequency oscillations due to signal-to-noise ratio imbalances. Chapter 4 explores experience-dependent plasticity, highlighting the role of thalamic synaptic inhibition in ocular dominance plasticity and the influence of cortical feedback. Chapter 5 investigates the involvement of endocannabinoids, particularly CB1 receptors, in inhibitory synaptic maturation and ocular dominance plasticity within the primary visual cortex.The general discussion raises the possibility of a link between neural plasticity and schizophrenia, particularly during the transformative phase of adolescence when the brain undergoes significant changes. An abnormal balance between inhibition and excitation, influenced by GABAergic maturation deficits, connectivity disruptions, and altered perceptual information transfer, may contribute to the development of schizophrenia.This thesis offers valuable insights into the intricate mechanisms underlying schizophrenia, with a particular focus on the CTC circuit, NMDA receptors, and endocannabinoids in the context of neuronal plasticity and cognitive function

The thalamocortical symphony:How thalamus and cortex play together in schizophrenia and plasticity

The work presented in this thesis aimed at investigating the function and mechanism of corticothalamic-thalamocortical network in schizophrenia and experience-dependent plasticity, further discussed their possible connection.In Chapter 2, we examined the effects of low-dose ketamine on the corticothalamic circuit (CTC) system. Our findings reveal that ketamine induces abnormal spindle activity and gamma oscillations in the CTC system. Notably, ketamine also leads to a transition in thalamic neurons from burst-firing to tonic action potential mode, which may underlie deficits in spindle oscillations. Chapter 3 addresses sensory perception deficits in schizophrenia, emphasizing disruptions in beta and gamma frequency oscillations due to signal-to-noise ratio imbalances. Chapter 4 explores experience-dependent plasticity, highlighting the role of thalamic synaptic inhibition in ocular dominance plasticity and the influence of cortical feedback. Chapter 5 investigates the involvement of endocannabinoids, particularly CB1 receptors, in inhibitory synaptic maturation and ocular dominance plasticity within the primary visual cortex.The general discussion raises the possibility of a link between neural plasticity and schizophrenia, particularly during the transformative phase of adolescence when the brain undergoes significant changes. An abnormal balance between inhibition and excitation, influenced by GABAergic maturation deficits, connectivity disruptions, and altered perceptual information transfer, may contribute to the development of schizophrenia.This thesis offers valuable insights into the intricate mechanisms underlying schizophrenia, with a particular focus on the CTC circuit, NMDA receptors, and endocannabinoids in the context of neuronal plasticity and cognitive function