In der vorliegenden Arbeit wurde erstmals mit Hilfe von drei unterschiedlichen experimentellen Modellen der Einfluß von Adrenomedullin (ADM) auf die myokardiale Kontraktilität des Rattenherzens untersucht. Die Methodik umfaßte die Verwendung des isolierten Herzen nach Langendorff, des isolierten Papillarmuskelpräparats und der konfokalen Laserscan Mikroskopie bei adulten Kardiomyozyten. In keinem der Ansätze konnte ein direkter Effekt von ADM auf die Kontraktilität nachgewiesen werden. An isolierten adulten Kardiomyozyten hatte ADM weder Einfluß auf die systolische Zellverkürzung noch auf den gleichzeitig registrierten zytosolischen Kalziumgehalt. Auch an isolierten Papillarmuskeln verursachte ADM keine Änderung der maximalen Kraftentwicklung oder Kraftanstiegsgeschwindigkeit. Endothelin-1 wurde sowohl am Papillarmuskelpräparat als auch an isolierten, adulten Kardiomyozyten als Positiv-Kontrolle verwendet und verursachte in beiden Versuchsaufbauten einen deutlichen Anstieg der kontraktilen Parameter. Als dritte Methode wurde das isoliert perfundierte Herz nach Langendorff verwendet. Unter Gabe von ADM zeigte sich ein Abfall des koronaren Perfusionsdrucks, entsprechend den bereits bekannten vasodilatierenden Eigenschaften des Peptids. Dieser Effekt war zwar begleitet von einer Abnahme der kontraktilen Parameter der Herzen, allerdings ist am isoliert und flußkonstant perfundierten Herz eine Abnahme des koronaren Perfusionsdrucks aufgrund des Gregg-Phänomes mit einer Abnahme der Kontraktilität vergesellschaftet. Aus den Ergebnissen dieser Arbeit kann daher der Schluß gezogen werden, das Adrenomedullin keinen Einfluß auf die Kontraktilität des Rattenherz hat. / The objective of this study was to investigate the influence of Adrenomedullin (ADM) on myocardial contractility of the rat heart in three different experimental models. First in the isolated rat heart preparation (Langendorf), second on the isolated papillary muscle preparation and third with confocal laserscan microscopy of isolated adult cardiomyocytes. None of these experimental models could show a direct effect of ADM on the contractility of the rat heart. In isolated adult cardiomyocytes, ADM had no influence on systolic cell shorting or on the simultaneously registered cytosolic calcium concentration. In isolated papillary muscle preparation ADM administration did not change maximal contractile force or time constants of contraction. Endothelin-1 was used as a positive control in both experimental setups and induced a marked increase in contraction parameters. In the isolated rat heart preparation (Langendorff), ADM induced a decrease of the coronary perfusion pressure, reflecting the already well described vasodilatatory properties of this peptide. This decrease was paralleled by a reduction of the contractile parameters of the heart, but in isolated rat heart preparations with constant coronary flow, a reduction of coronary perfusion pressure is always paralleled by a decrease of contractility due to the Gregg-Phenomenon. In conclusion the results of this study show that Adrenomedullin has no influence on myocardial contractility in the rat heart.

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools.

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools.