Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Shapes in vector fields : methods for continuous deformations and surface-based flow visualizations

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

Surface based hypothesis verification in intensity images using geometric and appearance data

In this paper we discuss current work concerning Appearance-based and CAD-based vision; two opposing vision strategies. CAD-based vision is geometry based, reliant on having complete object centred models. Appearance-based vision builds view dependent models from training images. Existing CAD-based vision systems that work with intensity images have all used one and zero dimensional features, for example lines, arcs, points and corners. We describe a system we have developed for combining these two strategies. Geometric models are extracted from a commercial CAD library of industry standard parts. Surface appearance characteristics are then learnt automatically by observing actual object instances. This information is combined with geometric information and is used in hypothesis evaluation. This augmented description improves the systems robustness to texture, specularities and other artifacts which are hard to model with geometry alone, whilst maintaining the advantages of a geometric description.

La dimensione frattale surface-based nelle neuroimmagini

La geometria frattale permette di definire un indice di complessitá strutturale di oggetti che presentano, fino a un certo livello d’ingrandimento, caratteristiche di auto-similaritá: il cervello umano ha un alto livello di complessitá, che cambia durante il corso della vita e con l’insorgenza di patologie. Tale complessitá puó essere descritta tramite la dimensione frattale (FD). L’obiettivo di questo elaborato ́e sviluppare un metodo di calcolo della FD surface-based, partendo dalla ricostruzione mediante mesh triangolari della superficie cerebrale. A questo scopo ́e stata implementata una procedura che utilizza gli strumenti di analisi di neuroimmagini, come FSL e FreeSurfer; l’algoritmo ́e stato validato su fantocci tridimensionali e testato su immagini di risonanza magnetica pesate in T1 del dataset International Consortium for Brain Mapping (ICBM), composto da 86 soggetti sani con etá compresa tra i 19 e gli 85 anni. Dalla ricerca condotta é emerso che il calcolo della FD surface-based restituisce valori accurati per i fantocci e permette di differenziare significativamnete gli uomini dalle donne. Concludendo, riteniamo che la FD surface-based si possa candidare come marcatore di complessitá strutturale nelle neuroimmagini, in modo complementare agli indici morfologici convenzionali.

Surface effect ferromagnetism in pure and reduced strontium titanate

A room temperature ferromagnetic hysteresis is observed in single crystal strontium titanate substrates as purchased from several manufacturers. It was found that polishing all sides of the substrates removed this observed hysteresis, suggesting that the origin of the ferromagnetic behavior resides on the surface of the substrates. X-ray diffraction and energy dispersive x-ray spectra were measured however they were unable to detect any impurity phases. In similar semiconducting oxides it was previously suggested that ferromagnetism could originate in oxygen vacancies or from disorder within the single crystal. To this end substrates were annealed in both air and vacuum in a range of temperatures (600°C to 1100°G) to both create bulk oxygen vacancies and to heal surface damage. Annealing in vacuum was found to create a measureable number of oxygen vacancies however their creation could not be correlated to the ferromagnetic signal of the substrate. Annealing in air was found to effect the remnant moment of the substrate as well as the width of the x-ray diffraction peaks on the unpolished face, weakly suggesting a relation between surface based disorder and ferromagnetism. Argon ion bombardment was employed to create a layer of surface disorder in the polished crystal, however it was not found to induce ferromagnetism. It was found that acid etching was sufficient to remove the ferromagnetism from as purchased samples and similarly simulated handling with stainless steel tweezers was sufficient to re-create the ferromagnetism. It is suggested that the origin of this ferromagnetism in SrTi03 is surface contaminants (mainly iron).

Cloud optical and microphysical properties derived from ground-based and satellite sensors over a site in the Yangtze Delta region

Comprehensive surface-based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in the central Yangtze Delta region, during a research campaign from May 2008 to December 2009. Cloud optical depth (COD), effective radius (Re), and liquid water path (LWP) were retrieved from measurements made with a suite of ground-based and spaceborne instruments, including an Analytical Spectral Devices spectroradiometer, a multi␣lter rotating shadowband radiometer, a multichannel microwave radiometer profiler, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes. Annual mean LWP, COD, and Re are 115.8 ± 90.8 g/m2, 28.5 ± 19.2, and 6.9 ± 4.2 microns. Over 90% of LWP values are less than 250 g/m2. Most of the COD values (>90%) fall between 5 and 60, and ~80% of Re values are less than 10 microns. Maximum (minimum) values of LWP and Re occur in summer (winter); COD is highest in winter and spring. Raining and nonraining clouds have signi␣cant differences in LWP, COD, and Re. Rainfall frequency is best correlated with LWP, followed by COD and Re. Cloud properties retrieved from multiple ground-based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD, and Re were -33.6 g/m2 (-26.4%), -5.8 (-31.4%), and 2.9 ␣m (29.3%) for 11 MODIS-Terra overpasses and -43.3 g/m2 (-22.3%), -3.0 (-10.0%), and -1.3 ␣m (-12.0%) for 8 MODIS-Aqua overpasses, respectively. These discrepancies indicate that MODIS cloud products still suffer from large uncertainties in this region.

Adsorption of organic molecules at the TiO2(110) surface: the effect of van der Waals interactions

Understanding the interaction of organic molecules with TiO2 surfaces is important for a wide range of technological applications. While density functional theory (DFT) calculations can provide valuable insight about these interactions, traditional DFT approaches with local exchange-correlation functionals suffer from a poor description of non-bonding van der Waals (vdW) interactions. We examine here the contribution of vdW forces to the interaction of small organic molecules (methane, methanol, formic acid and glycine) with the TiO2 (110) surface, based on DFT calculations with the optB88-vdW functional. The adsorption geometries and energies at different configurations were also obtained in the standard generalized gradient approximation (GGA-PBE) for comparison. We find that the optB88-vdW consistently gives shorter surface adsorbate-to-surface distances and slightly stronger interactions than PBE for the weak (physisorbed) modes of adsorption. In the case of strongly adsorbed (chemisorbed) molecules both functionals give similar results for the adsorption geometries, and also similar values of the relative energies between different chemisorption modes for each molecule. In particular both functionals predict that dissociative adsorption is more favourable than molecular adsorption for methanol, formic acid and glycine, in general agreement with experiment. The dissociation energies obtained from both functionals are also very similar, indicating that vdW interactions do not affect the thermodynamics of surface deprotonation. However, the optB88-vdW always predicts stronger adsorption than PBE. The comparison of the methanol adsorption energies with values obtained from a Redhead analysis of temperature programmed desorption data suggests that optB88-vdW significantly overestimates the adsorption strength, although we warn about the uncertainties involved in such comparisons.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2 . The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.

Kinetic and affinity analysis of hybridization reactions between PNA probes and DNA targets using surface plasmon field-enhanced fluorescence spectroscopy (SPFS)

Sequenz spezifische biomolekulare Analyseverfahren erweisen sich gerade im Hinblick auf das Humane Genom Projekt als äußerst nützlich in der Detektion von einzelnen Nukleotid Polymorphismen (SNPs) und zur Identifizierung von Genen. Auf Grund der hohen Anzahl von Basenpaaren, die zu analysieren sind, werden sensitive und effiziente Rastermethoden benötigt, welche dazu fähig sind, DNA-Proben in einer geeigneten Art und Weise zu bearbeiten. Die meisten Detektionsarten berücksichtigen die Interaktion einer verankerten Probe und des korrespondierenden Targets mit den Oberflächen. Die Analyse des kinetischen Verhaltens der Oligonukleotide auf der Sensoroberfläche ist infolgedessen von höchster Wichtigkeit für die Verbesserung bereits bekannter Detektions - Schemata. In letzter Zeit wurde die Oberflächen Plasmonen feld-verstärkte Fluoreszenz Spektroskopie (SPFS) entwickelt. Sie stellt eine kinetische Analyse - und Detektions - Methode dar, die mit doppelter Aufzeichnung, d.h. der Änderung der Reflektivität und des Fluoreszenzsignals, für das Interphasen Phänomen operiert. Durch die Verwendung von SPFS können Kinetikmessungen für die Hybridisierung zwischen Peptid Nukleinsäure (PNA), welche eine synthetisierte Nukleinsäure DNA imitiert und eine stabilere Doppelhelix formt, und DNA auf der Sensoroberfläche ausgeführt werden. Mittels einzel-, umfassend-, und titrations- Experimenten sowohl mit einer komplementär zusammenpassenden Sequenz als auch einer mismatch Sequenz können basierend auf dem Langmuir Modell die Geschwindigkeitskonstanten für die Bindungsreaktion des oligomer DNA Targets bzw. des PCR Targets zur PNA ermittelt werden. Darüber hinaus wurden die Einflüsse der Ionenstärke und der Temperatur für die PNA/DNA Hybridisierung in einer kinetischen Analyse aufgezeigt.