12,896 research outputs found

    Evaluation of Single-Chip, Real-Time Tomographic Data Processing on FPGA - SoC Devices

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    A novel approach to tomographic data processing has been developed and evaluated using the Jagiellonian PET (J-PET) scanner as an example. We propose a system in which there is no need for powerful, local to the scanner processing facility, capable to reconstruct images on the fly. Instead we introduce a Field Programmable Gate Array (FPGA) System-on-Chip (SoC) platform connected directly to data streams coming from the scanner, which can perform event building, filtering, coincidence search and Region-Of-Response (ROR) reconstruction by the programmable logic and visualization by the integrated processors. The platform significantly reduces data volume converting raw data to a list-mode representation, while generating visualization on the fly.Comment: IEEE Transactions on Medical Imaging, 17 May 201

    Optical tomography using the SCIRun problem solving environment: Preliminary results for three-dimensional geometries and parallel processing

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    We present a 3D implementation of the UCL imaging package for absorption and scatter reconstruction from time-resolved data (TOAST), embedded in the SCIRun interactive simulation and visualization package developed at the University of Utah. SCIRun is a scientific programming environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. While the capabilities of SCIRun's interactive approach are not yet fully exploited in the current TOAST implementation, an immediate benefit of the combined TOAST/SCIRun package is the availability of optimized parallel finite element forward solvers, and the use of SCIRun's existing 3D visualisation tools. A reconstruction of a segmented 3D head model is used as an example for demonstrating the capability of TOAST/SCIRun of simulating anatomically shaped meshes

    CMOS Vision Sensors: Embedding Computer Vision at Imaging Front-Ends

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    CMOS Image Sensors (CIS) are key for imaging technol-ogies. These chips are conceived for capturing opticalscenes focused on their surface, and for delivering elec-trical images, commonly in digital format. CISs may incor-porate intelligence; however, their smartness basicallyconcerns calibration, error correction and other similartasks. The term CVISs (CMOS VIsion Sensors) definesother class of sensor front-ends which are aimed at per-forming vision tasks right at the focal plane. They havebeen running under names such as computational imagesensors, vision sensors and silicon retinas, among others. CVIS and CISs are similar regarding physical imple-mentation. However, while inputs of both CIS and CVISare images captured by photo-sensors placed at thefocal-plane, CVISs primary outputs may not be imagesbut either image features or even decisions based on thespatial-temporal analysis of the scenes. We may hencestate that CVISs are more “intelligent” than CISs as theyfocus on information instead of on raw data. Actually,CVIS architectures capable of extracting and interpretingthe information contained in images, and prompting reac-tion commands thereof, have been explored for years inacademia, and industrial applications are recently ramp-ing up.One of the challenges of CVISs architects is incorporat-ing computer vision concepts into the design flow. Theendeavor is ambitious because imaging and computervision communities are rather disjoint groups talking dif-ferent languages. The Cellular Nonlinear Network Univer-sal Machine (CNNUM) paradigm, proposed by Profs.Chua and Roska, defined an adequate framework forsuch conciliation as it is particularly well suited for hard-ware-software co-design [1]-[4]. This paper overviewsCVISs chips that were conceived and prototyped at IMSEVision Lab over the past twenty years. Some of them fitthe CNNUM paradigm while others are tangential to it. Allthem employ per-pixel mixed-signal processing circuitryto achieve sensor-processing concurrency in the quest offast operation with reduced energy budget.Junta de Andalucía TIC 2012-2338Ministerio de Economía y Competitividad TEC 2015-66878-C3-1-R y TEC 2015-66878-C3-3-

    A Real-time Image Reconstruction System for Particle Treatment Planning Using Proton Computed Tomography (pCT)

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    Proton computed tomography (pCT) is a novel medical imaging modality for mapping the distribution of proton relative stopping power (RSP) in medical objects of interest. Compared to conventional X-ray computed tomography, where range uncertainty margins are around 3.5%, pCT has the potential to provide more accurate measurements to within 1%. This improved efficiency will be beneficial to proton-therapy planning and pre-treatment verification. A prototype pCT imaging device has recently been developed capable of rapidly acquiring low-dose proton radiographs of head-sized objects. We have also developed an advanced, fast image reconstruction software based on distributed computing that utilizes parallel processors and graphical processing units. The combination of fast data acquisition and fast image reconstruction will enable the availability of RSP images within minutes for use in clinical settings. The performance of our image reconstruction software has been evaluated using data collected by the prototype pCT scanner from several phantoms.Comment: Paper presented at Conference on the Application of Accelerators in Research and Industry, CAARI 2016, 30 October to 4 November 2016, Ft. Worth, TX, US

    GATE : a simulation toolkit for PET and SPECT

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    Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/

    Accelerated Modeling of Near and Far-Field Diffraction for Coronagraphic Optical Systems

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    Accurately predicting the performance of coronagraphs and tolerancing optical surfaces for high-contrast imaging requires a detailed accounting of diffraction effects. Unlike simple Fraunhofer diffraction modeling, near and far-field diffraction effects, such as the Talbot effect, are captured by plane-to-plane propagation using Fresnel and angular spectrum propagation. This approach requires a sequence of computationally intensive Fourier transforms and quadratic phase functions, which limit the design and aberration sensitivity parameter space which can be explored at high-fidelity in the course of coronagraph design. This study presents the results of optimizing the multi-surface propagation module of the open source Physical Optics Propagation in PYthon (POPPY) package. This optimization was performed by implementing and benchmarking Fourier transforms and array operations on graphics processing units, as well as optimizing multithreaded numerical calculations using the NumExpr python library where appropriate, to speed the end-to-end simulation of observatory and coronagraph optical systems. Using realistic systems, this study demonstrates a greater than five-fold decrease in wall-clock runtime over POPPY's previous implementation and describes opportunities for further improvements in diffraction modeling performance.Comment: Presented at SPIE ASTI 2018, Austin Texas. 11 pages, 6 figure

    The High Energy Telescope on EXIST

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    The Energetic X-ray Imaging Survey Telescope (EXIST) is a proposed next generation multi-wavelength survey mission. The primary instrument is a High Energy telescope (HET) that conducts the deepest survey for Gamma-ray Bursts (GRBs), obscured-accreting and dormant Supermassive Black Holes and Transients of all varieties for immediate followup studies by the two secondary instruments: a Soft X-ray Imager (SXI) and an Optical/Infrared Telescope (IRT). EXIST will explore the early Universe using high redshift GRBs as cosmic probes and survey black holes on all scales. The HET is a coded aperture telescope employing a large array of imaging CZT detectors (4.5 m^2, 0.6 mm pixel) and a hybrid Tungsten mask. We review the current HET concept which follows an intensive design revision by the HET imaging working group and the recent engineering studies in the Instrument and Mission Design Lab at the Goddard Space Flight Center. The HET will locate GRBs and transients quickly (<10-30 sec) and accurately (< 20") for rapid (< 1-3 min) onboard followup soft X-ray and optical/IR (0.3-2.2 micron) imaging and spectroscopy. The broad energy band (5-600 keV) and the wide field of view (~90 deg x 70 deg at 10% coding fraction) are optimal for capturing GRBs, obscured AGNs and rare transients. The continuous scan of the entire sky every 3 hours will establish a finely-sampled long-term history of many X-ray sources, opening up new possibilities for variability studies.Comment: 10 pages, 6 figures, 3 tables, SPIE conference proceedings (UV, X-ray, and Gamma-Ray Space Instrumentation for Astronomy XVI, 7435-9

    Silicon Drift Detector Readout Electronics for a Compton Camera

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    A prototype detector for Compton camera imaging is under development. A monolithic array of 19 channel Silicon drift detector with on-chip electronics is going to be used as a scatter detector for the prototype system. Custom designed analog and digital readout electronics for this detector was first tested by using a single cell Silicon drift detector. This paper describes the readout architecture and presents the results of the measurement.Comment: 10 pages, 9 figures, submitted to Nucl. Instr. Meth.
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