CeVis
  1. Center of Complex Systems and Visualization
  2. Lehre
  3. Oberseminar

In dem regelmäßig stattfindenden Oberseminar tragen Gäste aus aller Welt über Forschungsarbeiten zu Themen vor, die mit der Arbeit von CeVis und MeVis in Verbindung stehen, und Mitarbeiter von CeVis und MeVis präsentieren ihre neusten Ergebnisse.

Program for the Summer-Semester 2007

04.04.2007, 11:00
Novel methods for parameter based analysis of myocardial tissue in MR-Images
Date: 04.04.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Anja Hennemuth
MeVis Research

Novel methods for parameter based analysis of myocardial tissue in MR-Images

The analysis of myocardial tissue with contrast-enhanced MR delivers multiple parameters which can be used to classify the examined tissue. Perfusion images are often distorted by motion while late enhancement images are acquired with a different size and resolution. Therefore it is common to reduce the analysis to a visual inspection or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to deliver methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image. For the motion corrected perfusion sequence vector images containing the voxel enhancement curves semi-quantitative parameters are derived. The resulting vector images are completed with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose three different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Preliminary results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.

Anja Hennemuth , MeVis Research
04.04.2007, 11:30
Workflow oriented software support for image guided radiofrequency ablation of focal liver malignancies
Date: 04.04.2007
Time: 11:30:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Andreas Weihusen
MeVis Research

Workflow oriented software support for image guided radiofrequency ablation of focal liver malignancies

Image guided radiofrequency (RF) ablation has taken a significant part in the clinical routine as a minimally invasive method for the treatment of focal liver malignancies. Medical imaging is used in all parts of the clinical workflow of an RF ablation, incorporating treatment planning, interventional targeting and result assessment. This paper describes a software application, which has been designed to support the RF ablation workflow under consideration of the requirements of clinical routine, such as easy user interaction and a high degree of robust and fast automatic procedures, in order to keep the physician from spending too much time at the computer. The application therefore provides a collection of specialized image processing and visualization methods for treatment planning and result assessment. The algorithms are adapted to CT as well as to MR imaging. The planning support contains semi-automatic methods for the segmentation of liver tumors and the surrounding vascular system as well as an interactive virtual positioning of RF applicators and a concluding numerical estimation of the achievable heat distribution. The assessment of the ablation result is supported by the segmentation of the coagulative necrosis and an interactive registration of pre- and post-interventional image data for the comparison of tumor and necrosis segmentation masks. An automatic quantification of surface distances is performed to verify the embedding of the tumor area into the thermal lesion area. The visualization methods support representations in the commonly used orthogonal 2D view as well as in 3D scenes.

Andreas Weihusen , MeVis Research
11.04.2007, 11:00
Grid-Based Spectral Fiber Clustering
Date: 11.04.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Jan Klein
MeVis Research

Grid-Based Spectral Fiber Clustering

We introduce novel data structures and algorithms for clustering white matter fiber tracts to improve accuracy and robustness of existing techniques. Our novel fiber grid combined with a new randomized soft-division algorithm allows for defining the fiber similarity more precisely and efficiently than a feature space. A fine-tuning of several parameters to a particular fiber set - as it is often required if using a feature space - becomes obsolete.

The idea is to utilize a 3D grid where each fiber point is assigned to cells with a certain weight. From this grid, an affinity matrix representing the fiber similarity can be calculated very efficiently in time O(n) in the average case, where n denotes the number of fibers. This is superior to feature space methods which need O(n2) time. Our novel eigenvalue regression is capable of determining a reasonable number of clusters as it accounts for inter-cluster connectivity. It performs a linear regression of the eigenvalues of the affinity matrix to find the point of maximum curvature in a list of descending order. This allows for identifying inner clusters within coarse structures, which automatically and drastically reduces the a-priori knowledge required for achieving plausible clustering results. Our extended multiple eigenvector clustering exhibits a drastically improved robustness compared to the well known elongated clustering, which also includes an automatic detection of the number of clusters. We present several examples of artificial and real fiber sets clustered by our approach to support the clinical suitability and robustness of the proposed techniques.


Jan Klein , MeVis Research
11.04.2007, 11:30
Multispectral Brain Tumor Segmentation based on Histogram Model Adaptation
Date: 11.04.2007
Time: 11:30:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Jan Rexilius
MeVis Research

Multispectral Brain Tumor Segmentation based on Histogram Model Adaptation

Brain tumor segmentation and quantification from MR images is a challenging task. The boundary of a tumor and its volume are important parameters that can have direct impact on surgical treatment, radiation therapy, or on quantitative measurements of tumor regression rates. Although a wide range of different methods has already been proposed, a commonly accepted approach is not yet established. Today, the gold standard at many institutions still consists of a manual tumor outlining, which is potentially subjective, and a time consuming and tedious process.

We propose a new method that allows for fast multispectral segmentation of brain tumors. An efficient initialization of the segmentation is obtained using a novel probabilistic intensity model, followed by an iterative refinement of the initial segmentation. A progressive region growing that combines probability and distance information provides new, flexible tumor segmentation. In order to derive a robust model for brain tumors that can be easily applied to a new dataset, we retain information not on the anatomical, but on the global cross-subject intensity variability. Therefore, a set of multispectral histograms from different patient datasets is registered onto a reference histogram using global affine and non-rigid registration methods. The probability model is then generated from manual expert segmentations that are transferred to the histogram feature domain. A forward and backward transformation of a manual segmentation between histogram and image domain allows for a statistical analysis of the accuracy and robustness of the selected features. Experiments are carried out on patient datasets with different tumor shapes, sizes, locations, and internal texture.


Jan Rexilius , MeVis Research
20.04.2007, 11:00
Talk has been cancelled.
Prof. Vincent Heuveline , Universität Karlsruhe
02.05.2007, 11:00
Interaktive Mikromanipulation im Bereich der Mittelohrchirurgie
Date: 02.05.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Dipl. Ing. Carsten Lenze
Institut für komplexe integrierte Systeme und Mikrosensorik, Universität Oldenburg

Interaktive Mikromanipulation im Bereich der Mittelohrchirurgie

Der Vortrag behandelt ein innovatives Robotersystem für interaktive Fräs- und Manipulationsvorgänge am Mittelohr. Bei Eingriffen am Mittelohr kann es notwendig sein kraftintensive Fräsungen vorzunehmen und im Anschluss daran feine Positionierungsaufgaben durchzuführen. Dabei können Komplikationen wie zum Beispiel das Abrutschen und Verletzen von Nerven auftreten.

Das System Microassistant, welches in der Abteilung AMT der Universität Oldenburg entwickelt wurde, wird im Anschluss an den medizinischen Kontext vorgestellt. Die neuen Ansätze des Systems sind:

  • die Umsetzung einer neuartige Kraftmessung,
  • die Einbindung einer interaktive Steuerung des Systems,
  • die Entwicklung einer neuen Kinematikstruktur,
  • und die Implementierung einer adaptiven Registrierungskorrektur.
Neben dem Hauptfokus der Roboterkomponente des Microassistant wurde auch eine Navigationsumgebung implementiert. Als Sensorik zur Positionsmessung wurde dafür ein Stereokamerasystem verwendet, welches auch als Sensorik der neuartigen Kraftmessung verwendet wurde. Bei der interaktiven Steuerung ist herauszuheben, dass durch Aufbringen von Kräften über den Handballen eine Steuerung erreicht wird, welche dem Chirurgen ermöglicht beide Hände noch frei einzusetzen. Der Chirurg kann somit am Fräser nach wie vor Vibrationen des Fräsvorgangs wahrnehmen und die andere Hand z.B. zum Führen eines Saugers benutzen. Die Kinematikstruktur wurde als Parallelkinematik in neuartiger Form aufgebaut, wodurch eine hohe Steifigkeit erreicht wurde und eine hohe Präzision am Endeffektor realisiert wurde. Auf Basis der beschriebenen Kraftmessung wird im Weiteren auch eine Möglichkeit der intraoperativen Korrektur der Patienten-Bilddaten Registrierung vorgestellt. Experimente zur Evaluierung der Positioniergenauigkeit und der interaktiven Steuerung werden im Anschluss daran präsentiert. Am Ende des Vortrags wird noch ein kurzer Überblick über weitere Projekte unserer Arbeitsgruppe in Oldenburg gegeben.

Dipl. Ing. Carsten Lenze , Institut für komplexe integrierte Systeme und Mikrosensorik, Universität Oldenburg
03.05.2007, 11:00
DTI: Anwendung am Rückenmark und Phantomentwicklung
Date: 03.05.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Frederik Laun
DKFZ Heidelberg

DTI: Anwendung am Rückenmark und Phantomentwicklung

In dem Vortrag werden Methoden des MR - Diffusion Tensor Imaging (DTI) am Rückenmark und DTI-Phantome vorgestellt. Während DTI am Gehirn etabliert ist, gestaltet sich die Anwendung am Rückenmark schwieriger. Das Rückenmark ist recht klein (~1,5 cm), von pulsierendem CSF umgeben und die Magnetfeldverteilung ist aufgrund der vielen Gewebeübergänge sehr inhomogen. Diese Eigenschaften müssen bei der Sequenzentwicklung berücksichtigt werden. DTI Phantome ermöglichen Sequenzvalidierung und -optimierung. Phantome, die den MR- und Diffusionseigenschaftender weißen Substanz sehr nahe kommen werden vorgestellt.

Frederik Laun , DKFZ Heidelberg
07.05.2007, 11:00
X-ray Micro-Tomography and related clinical software development at EMU Sydney
Dr. Arndt Meier , EMU Sydney
09.05.2007, 14:00
Automating 4D CT Reconstruction of the human lung using Manifold Learning
Date: 09.05.2007
Time: 14:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Manfred Georg, BS
Washington University in St. Louis

Automating 4D CT Reconstruction of the human lung using Manifold Learning

Purpose: To automate the process of creating patientspecific 4D models of lung motion, using only CT image data despite varying and unknown patient breathing patterns.

Methods: Cine-captured CT data from 4D-CTs (16 slice volume at 17 couch positions from 25 time points) of lung cancer patients during free breathing were reconstructed into 25 3D data volumes of each couch position. A novel, manifold learning approach is used to assign a relative breathing phase to each of these data volumes. Relative breathing phases were aligned between successive couch positions by solving for an affine distortion of the parameterization of the images from each couch position. We chose the affine distortion that maximizes the first order continuity of the image data between neighboring couch positions. The complete 4D reconstruction is defined by choosing a sequence of 8 desired breathing phases and selecting the data volume from each couch position whose distorted parameter is closest to that breathing phase. A dense 4D motion field is computed throughout the 8 time step movie using standard SSD template tracking. The total motion of each tissue location is computed by discrete integration of this motion field through time.

Results: This fully automated process has been applied to 7 patients. The correlation coefficient between image manifold parameters and physiologic parameters of breathing (abdominal size) is 0.96 +/- 0.03. Representative frames from the 4D reconstruction are shown below.

Conclusion: Automated 4D reconstruction of free breathing CT scans is feasible using manifold learning techniques instead of physiologic breathing data.


Manfred Georg, BS , Washington University in St. Louis
10.05.2007, 14:00
Elastische Registrierung für die adaptive Strahlentherapie – Template Matching
Urban Malsch , DKFZ Heidelberg
16.05.2007, 11:00
Strukturierte Herzensangelegenheiten – Der MeVis Kardio-Explorer
Normel Müdeking , Hochschule Bremerhaven, MeVis Research
16.05.2007, 11:15
Jede Menge Leber – Eine medizinische Datenbank
Pawel Kolanek, Fabian Reim , Hochschule Bremerhaven, MeVis Research
16.05.2007, 11:30
Die Eingrenzung von Risiken von der med. Software DynaCAD 2.0. Ein Einblick in den Risikomanagementprozess vom Risikoplan bis zur Risikoanalyse.
Markus Sadina , Hochschule Bremerhaven, MeVis Research
23.05.2007, 11:00
Orientation Estimation and Image Enhancement
Date: 23.05.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Dr. Ola Friman
MeVis Research

Orientation Estimation and Image Enhancement

Local orientation is a fundamental spatial feature that is heavily utilized in biological visual systems, e.g., by the human brain. This fact has spawned much research in the image processing and computer vision communities, where local orientation now is a well known concept that comprises the basis of many successful algorithms for adaptive filtering, segmentation, registration, velocity estimation, corner detection, visualization and disparity estimation. In this talk, the basics of local orientation estimation and its representation using tensors will be explained. As an application, image enhancement, or adaptive filtering, will be demonstrated.

Dr. Ola Friman , MeVis Research
30.05.2007, 11:00
Optimal control of the thermistor problem
Date: 30.05.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Dr. Christian Meyer
WIAS Berlin

Optimal control of the thermistor problem

The talk is concerned with the optimal control of the temperature distribution in conductors heated up by means of the Joule effect. The model is mathematically described by a quasi-linear system of partial differential equations (PDEs) consisting of the instationary heat equation and an elliptic equation for the electric potential. First, we derive existence and uniqueness for the state system employing maximum parabolic and elliptic regularity and Banach's contraction principle. Afterwards, the associated linearized state system is discussed which allows to derive first-order necessary optimality conditions. Due to the presence of pointwise inequality constraints on the temperature, the corresponding Lagrange multipliers are in general regular Borel measures and appear as inhomogeneity in the adjoint system. Using a duality argument, one shows existence and uniqueness for the adjoint equations involving measures. Finally, our analysis is confirmed by an numerical example that deals with an application arising in the automotive industry. More precisely, we consider the hardening of a gear rack.

Dr. Christian Meyer , WIAS Berlin
05.06.2007, 11:00
Einstein and God
Date: 05.06.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Prof. Dr. Nathan Dean
Professor of Physics, Florida Atlantic UniversityVisiting Fellow, Faraday Institute of Science and Religion, Cambridge University.

Einstein and God

Albert Einstein, the greatest intellect of his age, was both a scientist and a humanist. His scientific reputation invested credibility in his opinions on ethics, morality and society. In this lecture, Dr. Nathan W. Dean will discuss Einstein’s own writings that are used to explore his views on the nature of God and the conclusions he reached regarding science, religion and humankind. Einstein's devotion to relativism and determinism in science are contrasted with the religious philosophy he publicly supported, as well as with the ethical and social judgments of his later years.

Prof. Dr. Nathan Dean , Professor of Physics, Florida Atlantic UniversityVisiting Fellow, Faraday Institute of Science and Religion, Cambridge University.
05.06.2007, 14:15
Entfernung von Kalkablagerungen zur Visualisierung von Bildern der Becken-Bein-CTA
Michael Herrmann , Universität Würzburg, Radiologie Mainz
06.06.2007, 11:00
TBA
PD Dr. Uwe Neubauer , Klinikum Bremen-Mitte
13.06.2007, 14:00
Simulation und Visualisierung in der Diagnostik und Behandlungsplanung bei zerebralen Aneurysmen
Date: 13.06.2007
Time: 14:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Prof. Dr. Bernhard Preim
Otto-von-Guericke-Universität Magdeburg

Simulation und Visualisierung in der Diagnostik und Behandlungsplanung bei zerebralen Aneurysmen

Die Entstehung und der Verlauf von Gefäßerkrankungen, wie Stenosen, Aneurysmen und Artherosklerose hängen offensichtlich stark von den Eigenschaften des Blutflusses, insbesondere der lokalen Wandscherspannung, des Gradienten der Wandscherspannung und den Flussmustern ab. Einer Vielzahl von Studien zufolge lässt sich das Rupturrisiko basierend auf einer Simulation des Blutflusses wesentlich besser bestimmen als anhand rein geometrischer Kriterien. Die Simulation dient auch dazu die Effekte verschiedener Behandlungsstrategien abzuschätzen. Simulation und Visualisierung müssen dabei eng miteinander verzahnt werden. Aufgabe der Visualisierung ist es einerseits akurate Oberflächenmodelle aus den medizinischen Bilddaten zu generieren, die zudem einige Randbedingungen in Bezug auf die Gitterqualität erfüllen müssen. Diese Modelle werden an geeigneten Stellen geclippt, um den zu simulierenden Bereich zu begrenzen und dienen als Eingabe für die Simulation. Die Visualisierung wird nach der Simulation genutzt, um die komplexen Ergebnisse adäquat darzustellen. Dabei liegt die Herausforderung darin, skalare und vektorielle Daten in ihrem zeitlichen Verlauf zu visualisieren. Während im Bereich der Modellgenerierung eigene Arbeiten der Magdeburger Gruppe vorliegen, bietet der Teil der Ergebnispräsentation im wesentlichen einen Überblick über existierende Arbeiten.

Prof. Dr. Bernhard Preim , Otto-von-Guericke-Universität Magdeburg
14.06.2007, 11:00
Visual Analyis of Perfusion Data
Date: 14.06.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Prof. Dr. Bernhard Preim
Otto-von-Guericke-Universität Magdeburg

Visual Analyis of Perfusion Data

We described the integration of statistical methods and visual exploration techniques for the analysis of the high-dimensional space of perfusion parameters, derived from medical perfusion data. The visual analysis strategy presented here allows to assess the reliablity of specific perfusion parameters, e.g. Time-To-Peak, the corelation of perfusion parameters in a particular case and thus enables an efficient evaluation focused on a significant subset of perfusion parameters. Compared to the prevailing purely visually and highly subjective evaluation methods, our approach enables a more reproducible evaluation supported by quantitative analysis results. Our research contributes to answering questions with respect to the diagnostic value of a certain combination of perfusion parameters. Such questions are debated in the medical research literature and they are difficult to treat, since the choice of specific imaging parameters strongly influence the diagnostic results. Our visual analysis approach thus may be used to investigate the effects of a new contrast agent, a new scheme of contrast agent administration or changes in other imaging parameters on the diagnostic value of perfusion parameter combinations.

The most important work to be done relates to a thourough evaluation of the presented analysis strategy for a larger number of specific cases in tumor, stroke and cardiac perfusion. Within such an evaluation, the perfusion data analysis and clinical parameters characterizing the progress of the respective disease have to be integrated to better understand the diagnostic value of perfusion parameters. Based on such an evaluation dedicated software systems for routine clinical diagnosis may be developed. Such systems must be fine-tuned to particular applications and should hide most of the


Prof. Dr. Bernhard Preim , Otto-von-Guericke-Universität Magdeburg
20.06.2007, 14:00
Adaptive Markov Models with Information-Theoretic Methods for Image Analysis
Date: 20.06.2007
Time: 14:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Prof. Dr. R. T. Whitaker
SCI, University of Utah

Adaptive Markov Models with Information-Theoretic Methods for Image Analysis

Low-level problems in image processing, such as denoising, reconstruction, and segmentation typically require some kind of model of image structure. Thus, the modeling images in a general, yet tractable manner remains an important area of research. Most image processing algorithms make strong geometric or statistical assumptions about the properties of the signal and/or noise. Therefore, they lack the generality to be easily applied to new applications or diverse image collections. This talk presents an adaptive Markov model of images that allows algorithms to automatically learn the local statistical dependencies of image neighborhoods. Probability densities for neighborhoods are estimated nonparametrically, through a kernel-based strategy, and thus, image statistics are captured through large sets of examples of image neighborhoods. We use this strategy to create adaptive algorithms for low-level image processing. We incorporate prior information, when available, using optimal Bayesian formulations. We enforce optimality criteria based on fundamental information-theoretic concepts that capture the functional dependence, information content, and uncertainty in the data. This talk presents examples of the application of this strategy to denoising, reconstruction, and segmentation.

Prof. Dr. R. T. Whitaker , SCI, University of Utah
04.07.2007, 11:00
Bildgebende Diagnostik des akuten Schlaganfalls (CT vs. MRT)
Dr. Benjamin Geisler , MeVis Research
11.07.2007, 11:00
Multi-scale modelling and homogenisation of reaction-diffusion processes
Date: 11.07.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Sebastian A. Meier and Malte A. Peter
Centre for Industrial Mathematics, FB 3, University of Bremen

Multi-scale modelling and homogenisation of reaction-diffusion processes

Many materials consist of several phases, i.e. they consist of two or more finely interwoven materials (with different physical and chemical properties). Typical examples are porous building materials like concrete and biological materials such as nacre and cell tissue. In order to describe the observable (macroscopic) properties of such composites, it is necessary to include information about the microscopic structure, i.e. knowledge about the interweavement or the pore structure in case of a porous material, as well as the properties of each component.

The talk is concerned with the general concepts of periodic homogenisation and two-scale modelling and their application to several reaction-diffusion processes arising in materials science and biological applications. Particular attention is paid to accounting for an evolution of the microstructure.


Sebastian A. Meier and Malte A. Peter , Centre for Industrial Mathematics, FB 3, University of Bremen
18.07.2007, 11:00
The Dynamics that Results From the Cooperation or Competition Between Groups
Date: 18.07.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Prof. Dr. Larry Liebovitch
Florida Atlantic University

The Dynamics that Results From the Cooperation or Competition Between Groups

Our interdisciplinary team of mediators, social psychologists, and physicists is studying conflicts at three levels: field studies in Africa and the Middle East, laboratory experiments with subjects, and mathematical models of conflict. A mathematical model can give us insight into which mechanisms are the most important in maintaining or resolving a conflict. In this model, the state of each of two parties depends on its own state in isolation, its previous state in time, its inertia to change, and the influence from the other party. We analyzed this model using analytical methods and numerical computer simulations. We show how the dynamics of the conflict depends on the positive feedback (cooperation), negative feedback (competition), or mixed positive and negative feedback between the parties.

Prof. Dr. Larry Liebovitch , Florida Atlantic University
01.08.2007, 11:00
Applications and Numerical Methods in High Dimension
Date: 01.08.2007
Time: 11:00:00
Place: CeVis/MeVis, Seminarraum Mandelbrot, UNI 29
Speaker: Dr. Carmeliza L. Navasca
Rochester Institute of Technology (RIT)

Applications and Numerical Methods in High Dimension

Standard methods for solving PDEs, for example, suffer from the "curse of dimensionality" since the computation grows exponentially as the state dimension increases. These equations in high dimension are important because they have real-world applications. In this talk, I will present some numerical techniques for solving optimal control problems in high dimension as well as describe recent tools, such as, tensor decomposition. In addition, I will feature some of its important applications in signal processing, pursuit-evasion games and parameter identification.

Dr. Carmeliza L. Navasca , Rochester Institute of Technology (RIT)
15.08.2007, 11:00
T2*-Relaxationszeiten: Perfusionmessung und Vessel Size Imaging
Dr. Peter Gall , Medizinischen Physik, Radiologie der Universitätklinik Freiburg

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