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A fast OS-type Bayesian reconstruction with an edge-preserving median prior

JOURNAL OF INSTRUMENTATION 2009年第7期4卷 P07012-P07012页

作者： Hsiao, I. -T. Huang, H. -M. Lin, K. -J. Chang Gung Univ Dept Med Imaging & Radiol Sci Kwei Shan Tao Yuan 333 Taiwan Chang Gung Mem Hosp Mol Imaging Ctr Kwei Shan Tao Yuan 333 Taiwan Case Western Reserve Univ Dept Biomed Engn Cleveland OH 44106 USA

We have previously proposed a new median prior ( MP) with edge-preserving and local monotonic properties using preconditioned conjugate gradient reconstruction algorithm (PCGMP). In our experience, PCG-MP is difficult to implement, and complex to adjust the hyper-parameters. To solve these problems, we applied a separable paraboloidal surrogate (SPS) [ 3] to MP and combined with a fast convergent OS-type algorithm, called COSEM. Based on preliminary studies, the new algorithm, MAPCOSEM-MP, showed similar performances in preserving edges as PCG-MP but the algorithm and the hyper-parameters of MAPCOSEM-MP is easier to tune up. To evaluate further the performance of MAPCOSEM-MP, we conducted the bias-variance studies using two phantoms with different conditions and then compared with MAPCOSEM-MM ( smoothing membrane prior). The preliminary results show that MP performs better for larger ROIs, while compatible to those of MM in smaller ROIs.

关键词： Image reconstruction in medical imaging data processing methods

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Improving noise characteristics using a modified image pyramid with guided filtering and Bayesian shrinkage threshold in low-dose animal radiography

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JOURNAL OF INSTRUMENTATION 2024年第3期19卷 C03011页

作者： Kim, Woosung Shim, Jiyong Lim, Younghwan Cho, Hyosung Han, Taehee Yonsei Univ Dept Radiat Convergence Engn 1 Yonseidae Gil Wonju 26493 South Korea Woorien Co 13 Samsung 1 Ro 2 Gil Hwaseong Si 18449 Gyeong Do South Korea

Radiography is a commonly used diagnostic tool in animal practice to provide clinical information. The recent market for animal radiography is rapidly growing owing to the increasing awareness of the welfare of companion animals and the expansion of animal clinics. As the clinical use of radiography in animal hospitals has grown rapidly, radiologists continuously seek ways to reduce the radiation dose to animals. This study proposes an effective noise removal method using a modified image pyramid with guided filtering and Bayesian shrinkage threshold for low -dose animal radiography. This study aims to model a modified image pyramid -based denoising algorithm and to confirm its applicability in an animal radiographic system. We conducted an experiment on a companion dog and cat using a commercially -available veterinary radiographic system and quantitatively evaluated the image quality using the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The PSNR and SSIM values measured in the denoised image of the dog using the proposed denoising algorithm were 39.54 and 0.96, respectively, which are improvements of approximately 11.3% and 5.5% of the values obtained in the original noisy image. Consequently, the proposed method is highly efficient in reducing image noise in animal radiography, thereby improving the image quality.

关键词： Image filtering data reduction methods data processing methods

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A wavelength-shifting-fibre-based scintillator neutron detector implemented with the median point calculation method

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JOURNAL OF INSTRUMENTATION 2012年第02期7卷 C02003-C02003页

作者： Nakamura, T. Kawasaki, T. Hosoya, T. Toh, K. Ebine, M. Birumachi, A. Sakasai, K. Soyama, K. Katagiri, M. Japan Atom Energy Agcy Mat & Life Sci Div J PARC Ctr Naka Ibaraki 3191195 Japan Ibaraki Univ Coll Engn Hitachi Ibaraki 3160033 Japan Japan Atom Energy Agcy Mech Engn & Elect Sect Nucl Sci Res Inst Naka Ibaraki 3191195 Japan

Median point calculation (MPC) method for scintillator neutron detectors operating in photon-counting mode has been developed. The method was applied to a wavelength-shifting (WLS)-fibre-based neutron detector in order to improve its pixel size and spatial resolution. The original detector was modified for a demonstration experiment performed using the SENJU neutron diffraction instrument at J-PARC (Japan Proton Accelerator Research Complex). The detector head comprised 64 x 2 WLS fibres arranged in the x and y directions at a pitch of 4 mm. The WLS fibres were sandwiched between two ZnS/(B2O3)-B-10 scintillator screens. The developed MPC method used the number of photons detected by each WLS fibre as a weight when calculating the positions of neutrons. The test detector implemented with the MPC method demonstrated that the effective pixel size and the spatial resolution were improved to 2 mm, corresponding to half the pitch of the WLS fibres.

关键词： data processing methods Neutron diffraction detectors Neutron detectors (cold, thermal, fast neutrons)

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Unfolding the background of secondary ions in measured nanodosimetric ionisation cluster size distributions

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JOURNAL OF INSTRUMENTATION 2019年第3期14卷 P03023-P03023页

作者： Hilgers, G. Bug, M. U. Rabus, H. Phys Tech Bundesanstalt Bundesallee 100 D-38116 Braunschweig Germany

Nanodosimetry is a methodology for quantifying the effects of ionising radiation on matter by determining the frequency distributions of the cluster size of ionisations in nanometric target volumes. In previous investigations with the Ion Counter nanodosimeter operated at PTB, significant deviations for large cluster sizes were found in the comparison between measured and simulated data of ionisation cluster size distributions. These deviations could be explained by a background of secondary ions, which are produced within the transport system of the ionised target molecules. In this paper, two different approaches were investigated to correct for the background of secondary ions in the measured data to obtain the "true" cluster size distribution to be used, e.g., in predictions of biological effectiveness. In the first approach, the correction of the background was treated as a minimising problem. In the second approach, an iterative unfolding algorithm using Bayes statistics was employed. In all cases where the convolution of the background-corrected results with the secondary ion background agrees well with the corresponding measured cluster size distribution, the background- correction led to an improved agreement between measurement and simulation. For the removal of a background of secondary ions from measured cluster size distributions, the unfolding algorithm using Bayes statistics is the preferred method as it proved to be the most effective and the least sensitive to boundary conditions. Moreover, it was considerably less time consuming.

关键词： data processing methods Microdosimetry and nanodosimetry

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Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

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JOURNAL OF INSTRUMENTATION 2009年第07期4卷 P07014-P07014页

作者： Karahaliou, A. Vassiou, K. Skiadopoulos, S. Kanavou, T. Yiakoumelos, A. Costaridou, L. Univ Patras Dept Med Phys Fac Med Patras 26500 Greece Univ Thessaly Dept Anat Fac Med Larisa 41110 Greece Univ Thessaly Dept Radiol Fac Med Larisa 41110 Greece

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960 +/- 0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

关键词： data processing methods Pattern recognition, cluster finding, calibration and fitting methods MRI (whole body, cardiovascular, breast, others), MR-angiography (MRA)

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Track Lab: extensible data acquisition software for fast pixel detectors, online analysis and automation

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JOURNAL OF INSTRUMENTATION 2024年第1期19卷 C01008页

作者： Manek, P. Burian, P. David-Bosne, E. Smolyanskiy, P. Bergmann, B. Czech Tech Univ Inst Expt & Appl Phys Husova 240-5 Prague 11000 Czech Republic UCL Dept Phys & Astron Gower St London WC1E 6BT England Univ West Bohemia Fac Elect Engn Univ 2795-26 Plzen 30100 Czech Republic

Fast, incremental evolution of physics instrumentation raises the question of efficient software abstraction and transferability of algorithms across similar technologies. This contribution aims to provide an answer by introducing Track Lab, a modern data acquisition program focusing on extensibility and high performance. Shipping with documented API and more than 20 standard modules, Track Lab allows complex analysis pipelines to be constructed from simple, reusable building blocks. Thanks to multi-threaded infrastructure, data can be clustered, filtered, aggregated and plotted concurrently in real-time. In addition, full hardware support for Timepix2, Timepix3 pixel detectors and embedded photomultiplier systems enables such analysis to be carried out online during data acquisition. Repetitive procedures can be automated with support for motorized stages and X-ray tubes. Freely distributed on 7 popular operating systems and 2 CPU architectures, Track Lab is a versatile tool for high energy physics research.

关键词： data acquisition concepts data processing methods Detector control systems (detector and experiment monitoring and slow-control systems, architecture, hardware, algorithms, databases) Pattern recognition, cluster finding, calibration and fitting methods

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The CMS experiment at the CERN LHC

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JOURNAL OF INSTRUMENTATION 2008年第08期3卷 S08004-S08004页

作者： Chatrchyan, S. Hmayakyan, G. Khachatryan, V. Sirunyan, A. M. Adam, W. Bauer, T. Bergauer, T. Bergauer, H. Dragicevic, M. Eroe, J. Friedl, M. Fruehwirth, R. Ghete, V. M. Glaser, P. Hartl, C. Hoermann, N. Hrubec, J. Haensel, S. Jeitler, M. Kastner, K. Krammer, M. de Abril, I. Magrans Markytan, M. Mikulec, I. Neuherz, B. Noebauer, T. Oberegger, M. Padrta, M. Pernicka, M. Porth, P. Rohringer, H. Schmid, S. Schreiner, T. Stark, R. Steininger, H. Strauss, J. Taurok, A. Uhl, D. Waltenberger, W. Walzel, G. Widl, E. Wulz, C. -E. Petrov, V. Prosolovich, V. Chekhovsky, V. Dvornikov, O. Emeliantchik, I. Litomin, A. Makarenko, V. Marfin, I. Mossolov, V. Shumeiko, N. Solin, A. Stefanovitch, R. Gonzalez, J. Suarez Tikhonov, A. Fedorov, A. Korzhik, M. Missevitch, O. Zuyeuski, R. Beaumont, W. Cardaci, M. De Langhe, E. De Wolf, E. A. Delmeire, E. Ochesanu, S. Tasevsky, M. Van Mechelen, P. D'Hondt, J. De Weirdt, S. Devroede, O. Goorens, R. Hannaert, S. Heyninck, J. Maes, J. Mozer, M. U. Tavernier, S. Van Doninck, W. Van Lancker, L. Van Mulders, P. Villella, I. Wastiels, C. Yu, C. Bouhali, O. Charaf, O. Clerbaux, B. De Harenne, P. De Lentdecker, G. Dewulf, J. P. Elgammal, S. Gindroz, R. Hammad, G. H. Mahmoud, T. Neukermans, L. Pins, M. Pins, R. Rugovac, S. Stefanescu, J. Sundararajan, V. Velde, C. Vander Vanlaer, P. Wickens, J. Tytgat, M. Assouak, S. Bonnet, J. L. Bruno, G. Caudron, J. De Callatay, B. De Jeneret, J. De Favereau De Visscher, S. Demin, P. Favart, D. Felix, C. Florins, B. Forton, E. Giammanco, A. Gregoire, G. Jonckman, M. Kcira, D. Keutgen, T. Lemaitre, V. Michotte, D. Militaru, O. Ovyn, S. Pierzchala, T. Piotrzkowski, K. Roberfroid, V. Rouby, X. Schul, N. Van der Aa, O. Beliy, N. Daubie, E. Herquet, P. Alves, G. Pol, M. E. Souza, M. H. G. Vaz, M. Damiao, D. De Jesus Oguri, V. Santoro, A. Sznajder, A. Gregores, E. De Moraes Iope, R. L. Novaes, S. F. Tomei, T. Anguelov, T. Antchev, G. Atanasov, I. Damgov, J. Darmenov, N. Dimitrov, L. Genchev, V. Iaydjiev, P. Marinov, A. Piperov, S. Stoykova, S. Sultanov, G. Trayanov, R. Univ Pisa Scuola Normale Super Pisa Pisa Italy Yerevan Phys Inst Yerevan 375036 Armenia Inst Hochenergiephys OeAW Vienna Austria Byelorussian State Univ Minsk BELARUS Natl Ctr Particle & High Energy Phys Minsk BELARUS Res Inst Nucl Problems Minsk BELARUS Univ Antwerp B-2020 Antwerp Belgium Vrije Univ Brussel Brussels Belgium Univ Libre Bruxelles Brussels Belgium Univ Ghent B-9000 Ghent Belgium Catholic Univ Louvain B-1348 Louvain Belgium Univ Mons B-7000 Mons Belgium Ctr Brasileiro Pesquisas Fis Rio De Janeiro Brazil Univ Fed Rio de Janeiro Inst Fis Rio De Janeiro Brazil Univ Estado Rio de Janeiro BR-20550011 Rio De Janeiro Brazil Univ Estadual Paulista Inst Fis Teor BR-01405 Sao Paulo Brazil Bulgarian Acad Sci Inst Nucl Res & Nucl Energy Sofia Bulgaria Univ Sofia BU-1126 Sofia Bulgaria Inst High Energy Phys Beijing 100039 Peoples R China Peking Univ Beijing 100871 Peoples R China Shanghai Inst Ceram Shanghai Peoples R China Univ Los Andes Bogota Colombia Tech Univ Split Split Croatia Univ Split Split Croatia Rudjer Boskovic Inst Zagreb Croatia Univ Cyprus Nicosia Cyprus NICPB Tallinn Estonia Aalto Univ Lab Adv Energy Syst FIN-02150 Espoo Finland Helsinki Inst Phys Helsinki Finland Lappeenranta Univ Technol Lappeenranta Finland CNRS IN2P3 Lab Annecy Le Vieux Phys Particules Annecy Le Vieux France CEA Saclay DSM DAPNIA F-91191 Gif Sur Yvette France Ecole Polytech CNRS IN2P3 Lab Leprince Ringuet F-91128 Palaiseau France Univ Strasbourg CNRS IN2P3 Inst Pluridisciplinaire Hubert Curien Strasbourg France Univ Haute Alsace Mulhouse Strasbourg France Univ Lyon 1 CNRS Inst Phys Nucl F-69622 Villeurbanne France Tbilisi State Univ Inst High Energy Phys & Informatizat GE-380086 Tbilisi Georgia Inst Phys Acad Sci Tbilisi Georgia Rhein Westfal TH Aachen Inst Phys 1 Aachen Germany Rhein Westfal TH Aachen Phys Inst A 3 Aachen Germany Rhein Westfal TH Aachen Phys Inst B 3 Aachen Germany DESY Hamburg Germany Univ Hamburg Inst

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

关键词： Instrumentation for particle accelerators and storage rings high energy Gaseous detectors Scintillators, scintillation and light emission processes Solid state detectors Calorimeters Gamma detectors Large detector systems for particle and astroparticle physics Particle identification methods Particle tracking detectors Spectrometers Analogue electronic circuits Control and monitor systems online data acquisition circuits data acquisition concepts Detector control systems Digital electronic circuits Digital signal processing Electronic detector readout concepts Front-end electronics for detector readout Modular electronics Online farms and online filtering Optical detector readout concepts Trigger concepts and systems VLSI circuits Analysis and statistical methods Computing data processing methods data reduction methods Pattern recognition, cluster finding, calibration and fitting methods Software architectures Detector alignment and calibration methods Detector cooling and thermo-stabilization Detector design and construction technologies and materials Detector grounding Manufacturing Overall mechanics design Special cables Voltage distributions

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Improved inference for the signal significance

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JOURNAL OF INSTRUMENTATION 2018年第12期13卷 P12011-P12011页

作者： Volobouev, I Trindade, D. A. Texas Tech Univ Dept Phys & Astron Lubbock TX 79409 USA Texas Tech Univ Dept Math & Stat Lubbock TX 79409 USA

XWe study the properties of several likelihood-based statistics commonly used in testing for the presence of a known signal under a mixture model with known background, but unknown signal fraction. Under the null hypothesis of no signal, all statistics follow a standard normal distribution in large samples, but substantial deviations can occur at practically relevant sample sizes. Approximations for respective p-values are derived to various orders of accuracy using the methodology of Edgeworth expansions. Adherence to normality is studied, and the magnitude of deviations is quantified according to resulting p-value inflation or deflation. We find that approximations to third-order accuracy are generally sufficient to guarantee p-values with nominal false positive error rates in the 5 sigma range (p-value = 2.87 x 10(-7)) for the classic Wald, score, and likelihood ratio (LR) statistics at relatively low sample sizes. Not only does LR have better adherence to normality, but it also consistently outperforms all other statistics in terms of false negative error rates. The reasons for this are shown to be connected with high-order cumulant behavior gleaned from fourth order Edgeworth expansions. Finally, a conservative procedure is suggested for making finite sample adjustments while accounting for the look elsewhere effect via the theory of random fields.

关键词： Analysis and statistical methods data processing methods

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A ROOT based event display software for JUNO

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JOURNAL OF INSTRUMENTATION 2018年第2期13卷 T02002-T02002页

作者： You, Z. Li, K. Zhang, Y. Zhu, J. Lin, T. Li, W. Sun Yat Sen Univ Guangzhou 510275 Guangdong Peoples R China Chinese Acad Sci Inst High Energy Phys Beijing 100049 Peoples R China

An event display software SERENA has been designed for the Jiangmen Underground Neutrino Observatory (JUNO). The software has been developed in the JUNO offline software system and is based on the ROOT display package EVE. It provides an essential tool to display detector and event data for better understanding of the processes in the detectors. The software has been widely used in JUNO detector optimization, simulation, reconstruction and physics study.

关键词： Software architectures (event data models, frameworks and databases) Neutrino detectors data processing methods Image filtering

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Fast GPU-based absolute intensity determination for energy-dispersive X-ray Laue diffraction

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JOURNAL OF INSTRUMENTATION 2016年第1期11卷 T01001-T01001页

作者： Alghabi, F. Send, S. Schipper, U. Abboud, A. Pietsch, U. Kolb, A. Univ Siegen Inst Vis & Graph Holderlinstr 3 D-57076 Siegen Germany Univ Siegen Solid State Phys Walter Flex Str 3 D-57072 Siegen Germany

This paper presents a novel method for fast determination of absolute intensities in the sites of Laue spots generated by a tetragonal hen egg-white lysozyme crystal after exposure to white synchrotron radiation during an energy-dispersive X-ray Laue diffraction experiment. The Laue spots are taken by means of an energy-dispersive X-ray 2D pnCCD detector. Current pnCCD detectors have a spatial resolution of 384 x 384 pixels of size 75 x 75 mu m(2) each and operate at a maximum of 400 Hz. Future devices are going to have higher spatial resolution and frame rates. The proposed method runs on a computer equipped with multiple Graphics processing Units (GPUs) which provide fast and parallel processing capabilities. Accordingly, our GPU-based algorithm exploits these capabilities to further analyse the Laue spots of the sample. The main contribution of the paper is therefore an alternative algorithm for determining absolute intensities of Laue spots which are themselves computed from a sequence of pnCCD frames. Moreover, a new method for integrating spectral peak intensities and improved background correction, a different way of calculating mean count rate of the background signal and also a new method for n-dimensional Poisson fitting are presented. We present a comparison of the quality of results from the GPU-based algorithm with the quality of results from a prior (base) algorithm running on CPU. This comparison shows that our algorithm is able to produce results with at least the same quality as the base algorithm. Furthermore, the GPU-based algorithm is able to speed up one of the most time-consuming parts of the base algorithm, which is n-dimensional Poisson fitting, by a factor of more than 3. Also, the entire procedure of extracting Laue spots' positions, energies and absolute intensities from a raw dataset of pnCCD frames is accelerated by a factor of more than 3.

关键词： data processing methods Pattern recognition, cluster finding, calibration and fitting methods Analysis and statistical methods

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