J.3 LIFE AND MEDICAL SCIENCES
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Radiologists from all application areas are trained to read slice-based visualizations of 3D medical image data. Despite the numerous
examples of sophisticated three-dimensional renderings, especially all variants of direct volume rendering, such methods are
often considered not very useful by radiologists who prefer slice-based visualization. Just recently there have been attempts to bridge this
gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking that result in repositioning slices.
In this paper, we present a new volume picking technique that, in contrast to previous work, does not require pre-segmented data or metadata. The positions picked by our method are solely based on the data itself, the transfer function and,
most importantly, on the way the volumetric rendering is perceived by viewers. To demonstrate the usefulness of the proposed method
we apply it for automatically
repositioning slices in an abdominal MRI
scan, a data set from a flow simulation and a number of other volumetric scalar fields. Furthermore we discuss how the method can be implemented in combination with various different volumetric rendering techniques.
Generierung hybrider Gitter für die Strömungssimulation auf komplexen anatomischen Geometrien
(2009)
Basierend auf einem vorhandenen Ansatz zur Einführung von anisotropen Tetraedern im Randbereich eines reinen Tetraedergitters wird ein Gittergenerator für hybride Gitter implementiert. Das hybride Gitter besteht in Randnähe primär aus anisotropen Prismen und im Inneren der Geometrie aus isotropen Tetraedern. Eine erhöhte Auflösung im Randbereich soll zu besseren Ergebnissen von numerischen Strömungssimulationen führen, für welche eine problemangepasste Diskretisierung des zu untersuchenden Gebietes benötigt wird. In dem zuvor genannten Ansatz wird eine Reihe von Übergangselementen vorgeschlagen, die an scharfen Kanten der Oberfläche platziert werden sollen. Im Rahmen dieser Diplomarbeit wird die Idee der Übergangselemente aufgegriffen und bei hybriden Gittern eingesetzt, um auch komplexe Eingabegeometrien vergittern zu können. Der ursprüngliche Gittergenerierungprozess wird überarbeitet und erweitert. Eine neue Menge an Übergangselementen wird eingeführt, es werden gekrümmte Extrusionsvektoren verwendet und es wird die Auswertung der medialen Oberfläche vorgenommen, um Überschneidungen im hybriden Gitter zu vermeiden. Der Gittergenerator wird als Modul in das Visualisierungs- und Analyseprogramm Amira implementiert und die erstellten hybriden Gitter werden auf ihre Elementqualität und die Güte der Strömungssimulationsergebnisse hin überprüft.
This work introduces novel internal and external memory algorithms for computing voxel skeletons of massive voxel objects with complex network-like architecture and for converting these voxel skeletons to piecewise linear geometry, that is triangle meshes and piecewise straight lines. The presented techniques help to tackle the challenge of visualizing and analyzing 3d images of increasing size and complexity, which are becoming more and more important in, for example, biological and medical research. Section 2.3.1 contributes to the theoretical foundations of thinning algorithms with a discussion of homotopic thinning in the grid cell model. The grid cell model explicitly represents a cell complex built of faces, edges, and vertices shared between voxels. A characterization of pairs of cells to be deleted is much simpler than characterizations of simple voxels were before. The grid cell model resolves topologically unclear voxel configurations at junctions and locked voxel configurations causing, for example, interior voxels in sets of non-simple voxels. A general conclusion is that the grid cell model is superior to indecomposable voxels for algorithms that need detailed control of topology. Section 2.3.2 introduces a noise-insensitive measure based on the geodesic distance along the boundary to compute two-dimensional skeletons. The measure is able to retain thin object structures if they are geometrically important while ignoring noise on the object's boundary. This combination of properties is not known of other measures. The measure is also used to guide erosion in a thinning process from the boundary towards lines centered within plate-like structures. Geodesic distance based quantities seem to be well suited to robustly identify one- and two-dimensional skeletons. Chapter 6 applies the method to visualization of bone micro-architecture. Chapter 3 describes a novel geometry generation scheme for representing voxel skeletons, which retracts voxel skeletons to piecewise linear geometry per dual cube. The generated triangle meshes and graphs provide a link to geometry processing and efficient rendering of voxel skeletons. The scheme creates non-closed surfaces with boundaries, which contain fewer triangles than a representation of voxel skeletons using closed surfaces like small cubes or iso-surfaces. A conclusion is that thinking specifically about voxel skeleton configurations instead of generic voxel configurations helps to deal with the topological implications. The geometry generation is one foundation of the applications presented in Chapter 6. Chapter 5 presents a novel external memory algorithm for distance ordered homotopic thinning. The presented method extends known algorithms for computing chamfer distance transformations and thinning to execute I/O-efficiently when input is larger than the available main memory. The applied block-wise decomposition schemes are quite simple. Yet it was necessary to carefully analyze effects of block boundaries to devise globally correct external memory variants of known algorithms. In general, doing so is superior to naive block-wise processing ignoring boundary effects. Chapter 6 applies the algorithms in a novel method based on confocal microscopy for quantitative study of micro-vascular networks in the field of microcirculation.
One crucial step in virtual drug design is the identification of new lead structures with respect to a pharmacological target molecule. The search for new lead structures is often done with the help of a pharmacophore, which carries the essential structural as well as physico-chemical properties that a molecule needs to have in order to bind to the target molecule. In the absence of the target molecule, such a pharmacophore can be established by comparison of a set of active compounds. In order to identify their common features,a multiple alignment of all or most of the active compounds is necessary. Moreover, since the “outer shape” of the molecules plays a major role in the interaction between drug and target, an alignment algorithm aiming at the identification of common binding properties needs to consider the molecule’s “outer shape”, which can be approximated by the solvent excluded surface. In this thesis, we present a new approach to molecular surface alignment based on a discrete representation of shape as well as physico-chemical properties by points distributed on the solvent excluded surface. We propose a new method to distribute points regularly on a surface w.r.t. a smoothly varying point density given on that surface. Since the point distribution algorithm is not restricted to molecular surfaces, it might also be of interest for other applications. For the computation of pairwise surface alignments, we extend an existing point matching scheme to surface points, and we develop an efficient data structure speeding up the computation by a factor of three. Moreover, we present an approach to compute multiple alignments from pairwise alignments, which is able to handle a large number of surface points. All algorithms are evaluated on two sets of molecules: eight thermolysin inhibitors and seven HIV-1 protease inhibitors. Finally, we compare the results obtained from surface alignment with the results obtained by applying an atom alignment approach.