This study demonstrates the value of historical aerial photographs as a source for monitoring long-term landslide evolution, which can be unlocked by using appropriate photogrammetric methods. The understanding of landslide mechanisms requires extensive data records; a literature review identified quantitative data on surface movements as a key element for their analysis. It is generally acknowledged that, owing to the flexibility and high degree of automation of modern digital photogrammetric techniques, it is possible to derive detailed quantitative data from aerial photographs. In spite of the relative ease of such techniques, there is only scarce research available on data quality that can be achieved using commonly available material, hence the motivation of this study. In two landslide case-studies (the Mam Tor and East Pentwyn landslides) the different types of products were explored, that can be derived from historical aerial photographs. These products comprised geomorphological maps, automatically derived elevation models (DEMs) and displacement vectors. They proved to be useful and sufficiently accurate for monitoring landslide evolution. Comparison with independent survey data showed good consistency, hence validating the techniques used. A wide range of imagery was used in terms of quality, media and format. Analysis of the combined datasets resulted in improvements to the stochastic model and establishment of a relationship between image ground resolution and data accuracy. Undetected systematic effects provided a limiting constraint to the accuracy of the derived data, but the datasets proved insufficient to quantify each factor individually. An important advancement in digital photogrammetry is image matching, which allows automation of various stages of the working chain. However, it appeared that the radiometric quality of historical images may not always assure good results, both for extracting DEMs and vectors using automatic methods. It can be concluded that the photographic archive can provide invaluable data for landslide studies, when modern photogrammetric techniques are being used. As ever, independent and appropriate checks should always be included in any photogrammetric design.

To estimate the delivered dose to the patient during intra-fraction or throughout the whole treatment, it is important to determine the contribution of dose accumulated at different patient geometries to the overall dose. Dose mapping utilizes deformable image registration to map doses deposited on patient geometries at different times. Inputs to the dose mapping process are the irradiated and reference images, the displacement vector field, and a dose mapping algorithm. Thus accuracy of the mapped dose depends on the DVF and dose mapping algorithm. Dose mapping had been the subject of many research studies however, up to now there is no gold standard DIR or dose mapping algorithm. This thesis compares current dose mapping algorithms under different conditions such as choosing the planning target and dose grid size, and introduces new tool to estimate the required spatial accuracy of a DVF. 11 lung patients were used for this thesis work. IMRT plans were generated on the end of inhale breathing phases with 66 Gy as the prescription dose. Demons DVF’s were generated using the Pinnacle treatment planning system DIR interface. Dtransform, Tri-linear with sub-voxel division, and Pinnacle dose mapping algorithms were compared to energy transfer with mass sub-voxel mapping. For breathing phase 50% on 11 patients, tissue density gradients were highest around the edge of the tumor compared to the CTV and the PTV edge voxels. Thus treatment plans generated with margin equal to zero on the tumor might yield the highest dose mapping error (DME). For plans generated on the tumor, there was no clinical effect of DME on the MLD, lung V20, and Esophagus volume indices. Statistically, MLD and lung V20 DME were significant. Two patients had D98 Pinnacle-DME of 4.4 and 1.2 Gy. In high dose gradient regions DVF spatial accuracy of ~ 1 mm is needed while 8 to 10 mm DVF accuracy can be tolerated before introducing any considerable dose mapping errors inside the CTV. By using ETM with mass sub-voxel mapping and adapting the reported DVF accuracy, the findings of this thesis have the potential to increase the accuracy of 4D lung planning.

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation. With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a model to formulate the motion through a mathematical function over time. [Li et al., 2011] uses principal component analysis (PCA) to propose one such model using each image as a long vector. However, the images come in a multidimensional arrays, and vectorization breaks the spatial structure. Driven by the needs to develop low-rank tensor decomposition and provided the 4DCT and Displacement Vector Field (DVF), we introduce two tensor decompositions, Population Value Decomposition (PVD) and Population Tucker Decomposition (PTD), to estimate the respiratory lung motion with high levels of accuracy and data compression. The first algorithm is a generalization of PVD [Crainiceanu et al., 2011] to higher order tensor. The second algorithm generalizes the concept of PVD using Tucker decomposition. Both algorithms are tested on clinical and phantom DVFs. New metrics for measuring the model performance are developed in our research. Results of the two new algorithms are compared to the result of the PCA algorithm.

Die vorliegende Arbeit beschaeftigt sich mit dem strukturellen Aufbau von (1-100) M-plane GaN, das mit plasmaunterstuetzter Molekularstrahlepitaxie auf gamma-LiAlO2(100) Substraten gewachsen wurde. Die heteroepitaktische Ausrichtung einerseits, sowie die Mikrostruktur und die Erzeugungsmechanismen der Defekte andererseits, wurde mit der Transmissionselektronenemikroskopie (TEM) systematisch untersucht. Das gamma-LiAlO2 Substrat reagiert heftig im Mikroskop unter Bestrahlung mit hochenergetischen Elektronen. Waehrend dieser Strahlenschaedigung verliert das Material seine urspruengliche kristalline Struktur und vollzieht eine Phasentransformation, die anhand einer Serie von Feinbereichsbeugungsdiagrammen nachgewiesen werden konnte. Die atomare Grenzflaechenstruktur zwischen epitaktisch gewachsenem alpha-GaN(1-100) und tetragonalem gamma-LiAlO2 Substrat ist mittels HRTEM untersucht worden. Die neuartige Epitaxiebeziehung ist mit Elektronenbeugung bestaetigt worden und lautet folgendermassen: (1-100)GaN liegt parallel zu (100)gamma-LiAlO2 und [11-20]GaN ist parallel zu [001]gamma-LiAlO2. Die Realstruktur der M-plane GaN Schichten, die auf (100)gamma-LiAlO2 gewachsen werden, unterscheidet sich erheblich von der in C-plane Orientierung hergestellten Epischichten. Ausfuehrliche TEM Untersuchungen zeigen, dass die M-plane Schichten vor allem intrinsische (I1 und I2) und extrinsische (E) Stapelfehler in der Basalebene enthalten. Der vorherrschende I2 Stapelfehler besitzt keine Komponente des Verschiebungsvektors senkrecht zur Ebene und ist damit nicht geeignet, epitaktische Dehnung entlang der [11-20] Richtung abzubauen. Darueberhinaus ist eine komplexe Grenze in der (10-10) Prismen- flaeche entdeckt worden, die zur Grenzflaeche geneigt verlaeuft. Die Defekte in den M-plane GaN Epischichten werden waehrend der anfaenglichen Keimbildungsphase erzeugt. Atomare Stufen entlang der [001] Richtung auf dem LiAlO2 Substrat fuehren zur Bildung von Stapelfehlern vom Typ I2. / In this work the structure of (1-100)M-plane GaN epitaxially grown on gamma-LiAlO2(100) by using plasmaassisted molecular beam epitaxy (PAMBE) is studied. The heteroepitaxial alignment and the microstructure of M-plane GaN as well as the defect formation in the layer are systematically investigated by using transmission electron microscopy (TEM). The gamma-LiALO2 substrate reacts under irradiation of high-energy electrons in the TEM (200-300 keV).The material looses its original crystalline structure during this process undergoing irradiation damage followed by a phase transformation as it is verified by a series of selected area diffraction patterns taken under constant electron dose. The result is a structural phase transformation from the tetragonal gamma to the trigonal alpha phase. The atomic interface structure of epitaxially grown hexagonal alpha-GaN(1-100) layers on tetragonal gamma-LiAlO2 (100) substrates is investigated by means of HRTEM. The novel epitaxial orientation relationship verified by electron diffraction is given by (1-100)GaN parallel to (100)gamma-LiAlO2 and [11-20]GaN parallel to [001]gamma-LiAlO2. The defect structure of M-plane GaN epilayers grown on gamma-LiAlO2(100) substrates is different to that of C-plane GaN. Our detailed TEM studies reveal that the M-plane layers mainly contain intrinsic I1 and I2 and extrinsic E basal plane stacking faults. The dominant I2 stacking fault has no out-of-plane displacement vector component and is thus not qualified for epitaxial strain relief along the [11-20] axis. Beyond this, a complex type of planar defect is detected in the (10-10) prism plane which is inclined with respect to the interface. The study of nucleation samples shows that the surface morphology is directly correlated to the generation of the dominant planar defects. Atomic steps along the [001] direction in the gamma-LiAlO2 substrate result in the formation of basal plane stacking faults I2.