Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer

Tissue Phenomics is the discipline of mining tissue images to identify patterns that are related to clinical outcome providing potential prognostic and predictive value. This involves the discovery process from assay development, image analysis, and data mining to the final interpretation and validation of the findings. Importantly, this process is not linear but allows backward steps and optimization loops over multiple sub-processes. We provide a detailed description of the Tissue Phenomics methodology while exemplifying each step on the application of prostate cancer recurrence prediction. In particular, we automatically identified tissue-based biomarkers having significant prognostic value for low-and intermediate-risk prostate cancer patients (Gleason scores 6-7b) after radical prostatectomy. We found that promising phenes were related to CD8(+) and CD68(+) cells in the microenvironment of cancerous glands in combination with the local micro-vascularization. Recurrence prediction based on the selected phenes yielded accuracies up to 83% thereby clearly outperforming prediction based on the Gleason score. Moreover, we compared different machine learning algorithms to combine the most relevant phenes resulting in increased accuracies of 88% for tumor progression prediction. These findings will be of potential use for future prognostic tests for prostate cancer patients and provide a proof-of-principle of the Tissue Phenomics approach

Variational Registration of Multiple Images with the SVD based SqN Distance Measure

Image registration, especially the quantification of image similarity, is an important task in image processing. Various approaches for the comparison of two images are discussed in the literature. However, although most of these approaches perform very well in a two image scenario, an extension to a multiple images scenario deserves attention. In this article, we discuss and compare registration methods for multiple images. Our key assumption is, that information about the singular values of a feature matrix of images can be used for alignment. We introduce, discuss and relate three recent approaches from the literature: the Schatten q-norm based SqN distance measure, a rank based approach, and a feature volume based approach. We also present results for typical applications such as dynamic image sequences or stacks of histological sections. Our results indicate that the SqN approach is in fact a suitable distance measure for image registration. Moreover, our examples also indicate that the results obtained by SqN are superior to those obtained by its competitors.Comment: 12 pages, 5 figures, accepted at the conference "Scale Space and Variational Methods" in Hofgeismar, Germany 201

IT-Security Status Evaluation

Im Rahmen dieser Arbeit wird ein Modell entwickelt, das den IT-Sicherheitsstatus eines Systems bewertet. Dabei werden Sicherheitskennzahlen basierend auf ISO-Standards entwickelt. Im Verlauf der Arbeit wird ein Überblick über das ISO Messmodell und über die Balanced Scorecard gegeben und für die Durchführung der Bewertung entsprechend modelliert. Abschließend runden die prototypische Implementierung und dessen Test die Arbeit ab. Die Bewertung des IT-Sicherheitsstatus von Systemen ist ein wichtiger Punkt in einem Unternehmen. Daher investieren diese immer mehr in die Sicherheit, um den Schutz vor Angriffen durch Hacker oder durch Schadprogramme zu gewährleisten. Aus diesem Grund ist eine regelmäßige Durchführung von Sicherheitsanalysen und Sicherheitsbewertungen von großer Bedeutung. In diesem Zusammenhang ist für die Bewertung der Sicherheitslage eines Unternehmens ein Framework erforderlich, das auf Best Practices und auf Standards basiert. Besonders hervorzuheben ist in diesem Kontext die Definition von Sicherheitskennzahlen. In der vorliegenden Arbeit wird zunächst ein Überblick über das Information Security Management System und über den Plan-Do-Act-Check Zyklus gegeben. Des Weiteren werden die Security Metrics und die Balanced Scorecard detailliert beschrieben. Die Zielsetzung dieser Arbeit ist es, mit Hilfe der definierten Sicherheitskennzahlen, den IT-Sicherheitsstatus eines Unternehmens zu messen und zu bewerten. Anhand von Sicherheitskennzahlen wird der Status der IT-Sicherheit im Unternehmen ermittelt. In dieser Arbeit werden Kennzahlen entwickelt, um die Zugriffskontrolle und die Sucheingaben im System zu bewerten. Dazu wird ein Plugin entwickelt und implementiert, das die Sicherheitsbewertung eines Systems automatisch durchführt. Dabei werden alle Login-Daten und Sucheingaben in einem bestimmten Zeitraum analysiert und bewertet. Um die IT-Sicherheitsbewertung durchführen zu können, ist auch ein Indikator erforderlich. Dieser wird vom Unternehmen bestimmt. Anhand der Bewertungsergebnisse wird ein Überblick über den IT-Sicherheitsstatus des Systems gegeben. Aufgrund dieser Ergebnisse kann das Unternehmen entscheiden, welche Maßnahmen bezüglich der Sicherheit im System getroffen werden müssen. Außerdem kann das Unternehmen detaillierte Informationen über Benutzernamen, Zeitpunkt und IP-Adresse aufrufen. Im Rahmen dieser Arbeit wird die Modellentwicklung, die Prototyp-Implementierung und die Testdurchführung ausführlich erklärt. Abschließend werden die Testergebnisse diskutiert.As part of this work, a model has been developed that evaluates the IT security status of a system. Security metrics are developed based on ISO standards. In the course of this work, an overview of the ISO measurement model and of the balanced scorecard is given and modeled accordingly for the performance of the evaluation. Finally, the prototype implementation and its test complete the work. Evaluating the security status of systems is an important issue in organizations. As a result, organizations are investing more and more in security to protect themselves against attacks by hackers or malware. For this reason, regular security analyses and security evaluations are important. In this context, assessing a company's security level requires a framework based on best practices and on standards. In this context the definition of security metrics is particularly highlighted. In the present work, an overview of the Information Security Management System and the Plan-Do-Act-Check cycle is given. There will also be a detailed description of the Security Metrics and the Balanced Scorecard. The objective of this thesis is to measure and evaluate the IT security status of a company with the aid of the defined security key figures. Security metrics are used to determine the status of IT security in the enterprise. In this work, metrics are developed to assess access control and search input in the system. For this purpose, a plugin is developed and implemented, which carries out the safety assessment of a system automatically. All login data and search entries are analyzed and evaluated within a certain period of time. To perform the IT security assessment, an indicator is also required. This is determined by the company. The evaluation results provide an overview of the IT security status of the system. Based on these findings, the company can decide what security measures to take to improve the system. In addition, the company can call up detailed information about user name, time and IP address. In the context of this work the model development, the prototype implementation and the test execution are explained in detail. Finally, the test results are discussed

Manifold learning for image-based breathing gating with application to 4D ultrasound

Breathing motion leads to a significant displacement and deformation of organs in the abdominal region. This makes the detection of the breathing phase for numerous applications necessary. We propose a new, purely image-based respiratory gating method for ultrasound. Further, we use this technique to provide a solution for breathing affected 4D ultrasound acquisitions with a wobbler probe. We achieve the gating with Laplacian eigenmaps, a manifold learning technique, to determine the low-dimensional manifold embedded in the high-dimensional image space. Since Laplacian eigenmaps assign each ultrasound frame a coordinate in low-dimensional space by respecting the neighborhood relationship, they are well suited for analyzing the breathing cycle. For the 4D application, we perform the manifold learning for each angle, and consecutively, align all the local curves and perform a curve fitting to achieve a globally consistent breathing signal. We performed the image-based gating on several 2D and 3D ultrasound datasets over time, and quantified its very good performance by comparing it to measurements from an external gating system

Stability of beams in steel eccentrically braced frames

When an eccentrically braced frame (EBF) is subjected to a severe seismic event, large axial force and bending moments are produced in the beam outside of the link Designers face significant difficulties in meeting the capacity design requirement to keep these beams elastic. On the other hand, previous research suggests that controlled yielding in the beams is not detrimental to EBF performance as long as stability of the beam is maintained. A computational study was undertaken to investigate the stability of cyclically loaded EBFs. A total of 51 EBF sub-assemblage models, none of which satisfies the capacity design requirement, were selected and investigated through three-dimensional, nonlinear finite element analysis. The results indicate that the link overstrength factor should be a function of the link length for performing capacity design of the beam outside of the link This is because flexure yielding links, which are more problematic to beam stability, tend to develop smaller overstrength compared to shear yielding links. Furthermore, designs with demand-to-capacity ratios greater than unity were found to be viable provided that the stability of the beam is maintained by making use of a slenderness limit developed herein

A new framework for morphological and morphometric study of fish species based on groupwise registration of otolith images.

Morphology of bones, teeth, and some particular structures are widely used for categorizing species and studying their evolution. In this paper, we used groupwise registration to provide a representative image from the set of the image samples that represents its typical morphology. We also provided perturbation map which indicates the deviation of each point through the morphology of structures in different species. The perturbation map can be further exploited for determining appropriate landmarks for morphometric analysis. Knowing the deformation between the prototype and each image sample from the species, the framework allows for automatic detection of corresponding points. Once the user puts a landmark on the prototype image, the corresponding points on all the image samples will be determined. This maximizes the accuracy in measuring the morphological indices by eliminating the human error due to uncertainty in locating landmarks