5 resultados para High-resolution aerial images
em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland
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The human striatum is a heterogeneous structure representing a major part of the dopamine (DA) system’s basal ganglia input and output. Positron emission tomography (PET) is a powerful tool for imaging DA neurotransmission. However, PET measurements suffer from bias caused by the low spatial resolution, especially when imaging small, D2/3 -rich structures such as the ventral striatum (VST). The brain dedicated high-resolution PET scanner, ECAT HRRT (Siemens Medical Solutions, Knoxville, TN, USA) has superior resolution capabilities than its predecessors. In the quantification of striatal D2/3 binding, the in vivo highly selective D2/3 antagonist [11C] raclopride is recognized as a well-validated tracer. The aim of this thesis was to use a traditional test-retest setting to evaluate the feasibility of utilizing the HRRT scanner for exploring not only small brain regions such as the VST but also low density D2/3 areas such as cortex. It was demonstrated that the measurement of striatal D2/3 binding was very reliable, even when studying small brain structures or prolonging the scanning interval. Furthermore, the cortical test-retest parameters displayed good to moderate reproducibility. For the first time in vivo, it was revealed that there are significant divergent rostrocaudal gradients of [11C]raclopride binding in striatal subregions. These results indicate that high-resolution [11C]raclopride PET is very reliable and its improved sensitivity means that it should be possible to detect the often very subtle changes occurring in DA transmission. Another major advantage is the possibility to measure simultaneously striatal and cortical areas. The divergent gradients of D2/3 binding may have functional significance and the average distribution binding could serve as the basis for a future database. Key words: dopamine, PET, HRRT, [11C]raclopride, striatum, VST, gradients, test-retest.
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PhotoAcoustic Imaging (PAI) is a branch in clinical and pre-clinical imaging, that refers to the techniques mapping acoustic signals caused by the absorption of the short laser pulse. This conversion of electromagnetic energy of the light to the mechanical (acoustic) energy is usually called photoacoustic effect. PAI, by combining optical excitation with acoustical detection, is able to preserve the diffraction limited spatial resolution. At the same time, the penetration depth is extended beyond the diffusive limit. The Laser-Scanning PhotoAcoustic Microscope system (LS-PAM) has been developed, that offers the axial resolution of 7.75 µm with the lateral resolution better than 10 µm. The first in vivo imaging experiments were carried out. Thus, in vivo label-free imaging of the mouse ear was performed. The principle possibility to image vessels located in deep layers of the mouse skin was shown. As well as that, a gold printing sample, vasculature of the Chick Chorioallantoic Membrane Assay, Drosophila larvae were imaged by PAI. During the experimental work, a totally new application of PAM was found, in which the acoustic waves, generated by incident light can be used for further imaging of another sample. In order to enhance the performance of the presented system two main recommendation can be offered. First, the current system should be transformed into reflection-mode setup system. Second, a more powerful source of light with the sufficient repetition rate should be introduced into the system.
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Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.