7,103 research outputs found

    A LabVIEW® based generic CT scanner control software platform

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    UGCT, the Centre for X-ray tomography at Ghent University (Belgium) does research on X-ray tomography and its applications. This includes the development and construction of state-of-the-art CT scanners for scientific research. Because these scanners are built for very different purposes they differ considerably in their physical implementations. However, they all share common principle functionality. In this context a generic software platform was developed using LabVIEW (R) in order to provide the same interface and functionality on all scanners. This article describes the concept and features of this software, and its potential for tomography in a research setting. The core concept is to rigorously separate the abstract operation of a CT scanner from its actual physical configuration. This separation is achieved by implementing a sender-listener architecture. The advantages are that the resulting software platform is generic, scalable, highly efficient, easy to develop and to extend, and that it can be deployed on future scanners with minimal effort

    The Estimation and Correction of Rigid Motion in Helical Computed Tomography

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    X-ray CT is a tomographic imaging tool used in medicine and industry. Although technological developments have significantly improved the performance of CT systems, the accuracy of images produced by state-of-the-art scanners is still often limited by artefacts due to object motion. To tackle this problem, a number of motion estimation and compensation methods have been proposed. However, no methods with the demonstrated ability to correct for rigid motion in helical CT scans appear to exist. The primary aims of this thesis were to develop and evaluate effective methods for the estimation and correction of arbitrary six degree-of-freedom rigid motion in helical CT. As a first step, a method was developed to accurately estimate object motion during CT scanning with an optical tracking system, which provided sub-millimetre positional accuracy. Subsequently a motion correction method, which is analogous to a method previously developed for SPECT, was adapted to CT. The principle is to restore projection consistency by modifying the source-detector orbit in response to the measured object motion and reconstruct from the modified orbit with an iterative reconstruction algorithm. The feasibility of this method was demonstrated with a rapidly moving brain phantom, and the efficacy of correcting for a range of human head motions acquired from healthy volunteers was evaluated in simulations. The methods developed were found to provide accurate and artefact-free motion corrected images with most types of head motion likely to be encountered in clinical CT imaging, provided that the motion was accurately known. The method was also applied to CT data acquired on a hybrid PET/CT scanner demonstrating its versatility. Its clinical value may be significant by reducing the need for repeat scans (and repeat radiation doses), anesthesia and sedation in patient groups prone to motion, including young children

    Extracting respiratory signals from thoracic cone beam CT projections

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    Patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principle component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely, the Amsterdam Shroud (AS) method, the intensity analysis (IA) method, and the Fourier-transform based phase analysis (FT-p) method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting respiratory signal. We also identified the applicability of each existing method.Comment: 21 pages, 11 figures, submitted to Phys. Med. Bio

    Micro-CT supporting structural analysis and modelling of ropes made of natural fibers

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    This paper describes the modelling of the structure and mechanical parameters of rope components made of natural fibers. Modern X-ray micro-tomography (Micro-CT) was employed to measure the parameters of the internal structure of the multi-component yarns making up rope and utilized as a basic model of twisted rope. The results allowed calculation of the tensions generated in the component yarns and detection of the unevenness of the filling of the component yarns by fibers, which was clearly visible in cross-section. The unevenness of twist measured as a function of distance from the center of the yarn was also detected. The unevenness of fiber distribution in the twisted element decreased its intensity, starting from the surface of the yarn and going deeper into the structure. Migration of the fibers in the frame of the circumference of the component yarns was associated with the mutual slide of single fibers
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