Multimodal Imaging of Silver Nanoclusters

Recent developments in Nanobiotechnology have given rise to a novel brand of fluorescent labels, fluorescent metal nanoclusters, e.g., gold and silver nanoclusters. Generally, high atomic number elements such as silver can attenuate more X-ray and consider as label in X-ray microtomography. Features such as ultra-small size, good biocompatibility, non-toxicity and photo-stability made nanoclusters more attractive as a fluorescent label than conventional fluorophores dye in biological imaging. The core concept of this thesis is to analyze silver nanoclusters as contrast agent by the multimodal imaging approaches of X-ray microtomography (MicroCT) and Optical Projection Tomography (OPT). To estimate the absorption and relation of X-ray and fluorescent signal by different concentrations of silver nanoclusters in samples. AgNCs-Agar with different concentrations of AgNCs, diluted with agar and water and filter paper coated with silver nanoclusters with different dipping time were studied in this work. The imaging implementation divided into three parts: 1. MicroCT imaging of samples (both AgNC-Agar and filter paper), 2. Optical imaging of AgNC-Agar samples by both fluorescent and bright-field modes. 3. MicroCT imaging of samples which were imaged by OPT first. Afterward, quantitative approach employed to both microCT and optical images to evaluate the relation between X-ray energy and light intensity with different concentrations of AgNCs to assess the amount of X-ray and light absorption by samples. Ideally, higher ratio of AgNCs revealed brighter microCT images due to more X-ray absorption. In sum, our results showed that the tested silver nanoclusters can be used as a label in both X-ray microtomography and fluorescent OPT since they show the contrast in X-ray and optical images. Moreover, depicted graphs demonstrate the linear correlation between data from images of both modalities and different amounts of silver material

Evaluation of state-of-the-art hardware architectures for fast cone-beam CT reconstruction

Holger Scherl introduces the reader to the reconstruction problem in computed tomography and its major scientific challenges that range from computational efficiency to the fulfillment of Tuy's sufficiency condition. The assessed hardware architectures include multi- and many-core systems, cell broadband engine architecture, graphics processing units, and field programmable gate arrays

FPGA implementations for parallel multidimensional filtering algorithms

PhD ThesisOne and multi dimensional raw data collections introduce noise and artifacts, which need to be recovered from degradations by an automated filtering system before, further machine analysis. The need for automating wide-ranged filtering applications necessitates the design of generic filtering architectures, together with the development of multidimensional and extensive convolution operators. Consequently, the aim of this thesis is to investigate the problem of automated construction of a generic parallel filtering system. Serving this goal, performance-efficient FPGA implementation architectures are developed to realize parallel one/multi-dimensional filtering algorithms. The proposed generic architectures provide a mechanism for fast FPGA prototyping of high performance computations to obtain efficiently implemented performance indices of area, speed, dynamic power, throughput and computation rates, as a complete package. These parallel filtering algorithms and their automated generic architectures tackle the major bottlenecks and limitations of existing multiprocessor systems in wordlength, input data segmentation, boundary conditions as well as inter-processor communications, in order to support high data throughput real-time applications of low-power architectures using a Xilinx Virtex-6 FPGA board. For one-dimensional raw signal filtering case, mathematical model and architectural development of the generalized parallel 1-D filtering algorithms are presented using the 1-D block filtering method. Five generic architectures are implemented on a Virtex-6 ML605 board, evaluated and compared. A complete set of results on area, speed, power, throughput and computation rates are obtained and discussed as performance indices for the 1-D convolution architectures. A successful application of parallel 1-D cross-correlation is demonstrated. For two dimensional greyscale/colour image processing cases, new parallel 2-D/3-D filtering algorithms are presented and mathematically modelled using input decimation and output image reconstruction by interpolation. Ten generic architectures are implemented on the Virtex-6 ML605 board, evaluated and compared. Key results on area, speed, power, throughput and computation rate are obtained and discussed as performance indices for the 2-D convolution architectures. 2-D image reconfigurable processors are developed and implemented using single, dual and quad MAC FIR units. 3-D Colour image processors are devised to act as 3-D colour filtering engines. A 2-D cross-correlator parallel engine is successfully developed as a parallel 2-D matched filtering algorithm for locating any MRI slice within a MRI data stack library. Twelve 3-D MRI filtering operators are plugged in and adapted to be suitable for biomedical imaging, including 3-D edge operators and 3-D noise smoothing operators. Since three dimensional greyscale/colour volumetric image applications are computationally intensive, a new parallel 3-D/4-D filtering algorithm is presented and mathematically modelled using volumetric data image segmentation by decimation and output reconstruction by interpolation, after simultaneously and independently performing 3-D filtering. Eight generic architectures are developed and implemented on the Virtex-6 board, including 3-D spatial and FFT convolution architectures. Fourteen 3-D MRI filtering operators are plugged and adapted for this particular biomedical imaging application, including 3-D edge operators and 3-D noise smoothing operators. Three successful applications are presented in 4-D colour MRI (fMRI) filtering processors, k-space MRI volume data filter and 3-D cross-correlator.IRAQI Government