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Relevant bibliographies by topics / Medipix3

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Journal articles
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Academic literature on the topic 'Medipix3'

Author: Grafiati

Published: 29 June 2021

Last updated: 15 February 2022

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Journal articles on the topic "Medipix3"

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Gimenez, Eva N., Rafael Ballabriga, Gabriel Blaj, Michael Campbell, Igor Dolbnya, Erik Frodjh, Ian Horswell, et al. "Medipix3RX: Characterizing the Medipix3 Redesign With Synchrotron Radiation." IEEE Transactions on Nuclear Science 62, no. 3 (June 2015): 1413–21. http://dx.doi.org/10.1109/tns.2015.2425227.

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Procz, S., K. A. Wartig, A. Fauler, A. Zwerger, J. Luebke, R. Ballabriga, G. Blaj, M. Campbell, M. Mix, and M. Fiederle. "Medipix3 CT for material sciences." Journal of Instrumentation 8, no. 01 (January 16, 2013): C01025. http://dx.doi.org/10.1088/1748-0221/8/01/c01025.

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Gimenez, Eva N., Rafael Ballabriga, Michael Campbell, Ian Horswell, Xavier Llopart, Julien Marchal, Kawal J. S. Sawhney, Nicola Tartoni, and Daniel Turecek. "Characterization of Medipix3 With Synchrotron Radiation." IEEE Transactions on Nuclear Science 58, no. 1 (February 2011): 323–32. http://dx.doi.org/10.1109/tns.2010.2089062.

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Turecek, D., T. Holy, J. Jakubek, S. Pospisil, and Z. Vykydal. "Pixelman: a multi-platform data acquisition and processing software package for Medipix2, Timepix and Medipix3 detectors." Journal of Instrumentation 6, no. 01 (January 11, 2011): C01046. http://dx.doi.org/10.1088/1748-0221/6/01/c01046.

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Pennicard, D., S. Lange, S. Smoljanin, H. Hirsemann, and H. Graafsma. "LAMBDA — Large Area Medipix3-Based Detector Array." Journal of Instrumentation 7, no. 11 (November 27, 2012): C11009. http://dx.doi.org/10.1088/1748-0221/7/11/c11009.

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Ballabriga, R., G. Blaj, M. Campbell, M. Fiederle, D. Greiffenberg, E. H. M. Heijne, X. Llopart, et al. "Characterization of the Medipix3 pixel readout chip." Journal of Instrumentation 6, no. 01 (January 11, 2011): C01052. http://dx.doi.org/10.1088/1748-0221/6/01/c01052.

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Tencé, Marcel, Jean-Denis Blazit, Xiaoyan Li, Matus Krajnak, Eduardo Nebot del Busto, Richard Skogeby, Léo Cambou, Mathieu Kociak, Odile Stephan, and Alexandre Gloter. "Electron Energy-loss Spectroscopy Using MerlinEM - Medipix3 Detector." Microscopy and Microanalysis 26, S2 (July 30, 2020): 1940–42. http://dx.doi.org/10.1017/s1431927620019881.

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Doesburg, R. M. N., T. Koenig, S. J. Nik, S. T. Bell, J. P. Ronaldson, M. F. Walsh, A. P. H. Butler, and P. H. Butler. "Spectrum measurement using Medipix3 in Charge Summing Mode." Journal of Instrumentation 7, no. 11 (November 15, 2012): C11004. http://dx.doi.org/10.1088/1748-0221/7/11/c11004.

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Plackett, R., I. Horswell, E. N. Gimenez, J. Marchal, D. Omar, and N. Tartoni. "Merlin: a fast versatile readout system for Medipix3." Journal of Instrumentation 8, no. 01 (January 23, 2013): C01038. http://dx.doi.org/10.1088/1748-0221/8/01/c01038.

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Visser, J., M. van Beuzekom, Henk Boterenbrood, B. van der Heijden, J. I. Muñoz, S. Kulis, B. Munneke, and F. Schreuder. "SPIDR: a read-out system for Medipix3 & Timepix3." Journal of Instrumentation 10, no. 12 (December 29, 2015): C12028. http://dx.doi.org/10.1088/1748-0221/10/12/c12028.

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Dissertations / Theses on the topic "Medipix3"

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Procz, Szymon [Verfasser], and Michael [Akademischer Betreuer] Fiederle. "Hochauflösende Computertomographie mit Medipix3-Halbleiterdetektoren." Freiburg : Universität, 2012. http://d-nb.info/1122742363/34.

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Lübke, Jördis [Verfasser], and Michael [Akademischer Betreuer] Fiederle. "Entwicklung eines iterativen Rekonstruktionsverfahrens für einen Medipix3-Computertomographen." Freiburg : Universität, 2011. http://d-nb.info/1122592205/34.

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Jabar, Alia. "Karaktärisering av spatial upplösning i röntgenmikroskopi." Thesis, Mittuniversitetet, Institutionen för elektronikkonstruktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42387.

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X-ray imaging was a very important detection that is used in many useful functionalities as in healthcare. It would be powerful and facilitate several functions if we could come up with a method that gives a better resolution when doing X-ray imaging. This will be done by using two different detectors, a commercial detector (Innocare) and a direct converting detector (Medipix3). These two detectors have different properties. In addition to these detectors, a radiation source that radiates with X-rays has been used and a line mask that provides the ability to read the resolution of the image. The use of these detectors will provide answers to the investigation of limitations that its detectors have.
Röntgenavbildning är en viktig upptäckt som används i bland annat vården. Det skulle underlätta flera användningsområden om en metod kunde tas fram som ger bättre upplösning på bilder vid avbildning. I detta arbete undersöks vad som kan bidra till att få den bästa upplösningen vid röntgenavbildning. I undersökningen kommer det att användas två olika detektorer, en kommersiell detektor (Innocare) och en direktkonverterande detektor (Medipix3). Dessa två detektorer har olika egenskaper. Utöver dessa detektorer har en strålkälla som strålar med röntgenstrålar använts och en linjemask som ger möjligheten att läsa av bildens upplösning. Användningen av dessa detektorer kommer att ge svar på utredningen av begränsningar som dess detektorer har.

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Sedayo, Anas. "Clinical applications of the Medipix detector." Thesis, University of Canterbury. Physics and astronomy, 2012. http://hdl.handle.net/10092/7229.

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In this thesis a recently developed energy resolving x-ray detector (Medipix) is used to investigate potential medical applications of spectral x-ray imaging. Computed Tomography (CT) is one of the most important medical imaging modalities. Recent developments in CT techniques include dual-energy CT, where images are taken with two different x-ray spectra by either using two x-ray tubes operated at different voltages, or modulating the operating voltage of a single tube. These techniques provide spectral information in the CT dataset but are limited to what can be achieved by manipulating the x-ray source, since the detectors used in current CT systems are unable to provide spectral information about the detected x-rays. A preliminary investigation of the use of the Medipix detectors for two different medical applications is presented. The first, applications is imaging of blood vessels for diagnosis of vascular diseases, and the second, characterising and measuring the energy dependence of x-ray attenuation in fat and liver tissue using the Medipix2 detector. This second investigation is part of work towards (eventually) quantifying the fat content of liver tissue in vivo, which is important for the early diagnosis of fatty liver disease. While an early attempt to identify iron fluorescence x-rays in a Monte-Carlo simulation of blood vessel x-ray image was not successful, the potential for improving image contrast using the changes in x-ray attenuation at the iodine k-edge iodine have been investigated in a series of further simulations and appears to be feasible. The potential use of spectral imaging to differentiate and quantify tissues without the need for added contrast material has been investigated by using a Medipix2 detector to measure the energy dependence of x-ray absorption in fat and liver tissue. The results of this experimental work show significant differences in x-ray attenuation between these two tissues that suggest this form of spectral imaging may be useful in practice.

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Pichotka, Martin Peter [Verfasser], and Caroline [Akademischer Betreuer] Röhr. "Iterative CBCT reconstruction-algorithms for a spectroscopic Medipix-Micro-CT = Iterative CBCT Rekonstruktions-Algorithmen für ein spektroskopisches Medipix-Mikro-CT." Freiburg : Universität, 2014. http://d-nb.info/1115495674/34.

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Butzer, Jochen Sieghard. "MARS-CT: Biomedical Spectral X-ray Imaging with Medipix." Thesis, University of Canterbury. Physics and Astronomy, 2009. http://hdl.handle.net/10092/3863.

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Computed Tomography is one of the most important image modalities in medical imaging nowadays. Recent developments have led to a new acquisition technique called 'dual-energy', where images are taken with different x-ray spectra. This enables for the first time spectral information in the CT dataset. Our approach was to use an energy resolving detector (Medipix) and investigate its potential in the medical imaging domain. Images are taken in different energy bins. For acquisition of the data, a CT scanner called 'Medipix All Resolution System' (MARS) scanner was constructed. It was upgraded to achieve better image quality as well as faster scan time and a stable operation. In medical imaging, it is important to achieve a high contrast and a good detail recognition at a low dose. Therefore, it is common practice to use contrast agents to highlight certain regions of the body like e.g. the vascular system. But with a broad spectrum acquisition, it is often impossible to distinguish highly absorbing body elements like bones from the contrast agent. We target this problem by a contrast agent study using different energy bins. This so called spectral contrast agent study has been conducted with small animals using the MARS scanner. The data has been processed to create an optimal CT reconstruction. The image enhancement techniques consist of corrections for noisy pixels, intensity fluctuations and eliminating streaks in the sinograms to reduce ring artifacts. In order to evaluate the data, we used two methods of material identification. The material reconstruction method works on projection data and uses a maximum-likelihood estimation to reconstruct images of base materials. The second method, the principal component analysis (PCA), identifies the relevant information from the spectral dataset in a few derived variables that account for most of the variance in the dataset. This resulted in images with enhanced contrast and removed redundancies. It is possible to combine these images in one colour image where anatomical structures are shown in good detail and certain materials show up in different colors. Based on this new information from spectral data, we could show that it is possible to distinguish the spinal bone from contrast agent.

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Mitschke, Michaela. "Evaluation of different sensor materials for the medipix X-ray detectors." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980697735.

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Korn, Alexander. "Spektrale und bildgebende Eigenschaften photonenzählender Röntgendetektoren am Beispiel des Medipix-Detektors." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=984391622.

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Zainon, Rafidah Binti. "Spectral Micro-CT Imaging of Ex Vivo Atherosclerotic Plaque." Thesis, University of Canterbury. Physics and Astronomy, 2012. http://hdl.handle.net/10092/7165.

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The goal of this research was to demonstrate the potential of spectral CT for the discrimination of vulnerable atherosclerotic plaques. It was proposed that spectral CT has the potential to identify the presence of specific markers for vulnerable plaques: iron deposits and lipid core. A spectral micro-CT system incorporating the latest Medipix spectroscopic photon- counting detectors was commissioned for this purpose. Using spectroscopic methods developed with this system, it was possible to distinguish the presence of iron deposits and lipid core within ex vivo atherosclerotic plaques. Atherosclerosis or hardening of arteries is a systemic disease of the vessel wall that occurs in the aorta, carotid, coronary and peripheral arteries. It is characterised by the deposition of calcified plaques on the innermost layer of the artery wall. Vulnerable plaques are unstable, prone to rupture and put the person at risk of cardiovascular events and strokes. Factors that may lead to plaque instability are lipid content and iron deposits. This preclinical study is a precursor to the development of a clinical technique that will enable vulnerable atherosclerotic plaques to be identified in vivo prior to treatment or removal. Following a preliminary study on atherosclerotic plaques with a prototype system, the MARS-CT3 spectral micro-CT system incorporating Medipix3 was developed and commissioned for further plaque studies. The spectral CT data sets acquired by this system were assessed visually for morphology and analysed for material composition using a linear algebra method. The results were correlated with photography and histology (the histology is the current gold standard). The presence of iron and lipid can be differentiated from the background soft-tissue using a linear algebra method. However the quantification of iron in the presence of calcium is not currently possible without additional data or constraints. Nevertheless the presence of iron deposits within the plaques can be distinguished in the high resolution MARS-CT images and has been correlated with photographic and histological evidence. Thus, using the high spatial resolution spectral data from MARS-CT, the discrimination of lipid core and iron deposits within ex vivo advanced human atherosclerotic plaques is feasible. This may provide the basis for the development of a clinical technique that will identify vulnerable plaques in vivo by high resolution spectral CT.

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Tang, Dikai Nate. "MARS Spectral CT: Image quality performance parameters using the Medipix3.0 detector." Thesis, University of Canterbury. Department of Physics and Astronomy, 2013. http://hdl.handle.net/10092/7828.

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The research in this thesis was undertaken because information on the relationship between scan parameters and image quality for the MARS spectral CT was lacking. However, the MARS spectral CT is expected to extend into clinical use in the future, so it is absolutely crucial that we know how the quality of the images that it produces is effected by different can parameters. This will allow us to make further improvements to the machine, and ultimately help clinicians to visualise important information in patients which are not revealed by other imaging modalities. This thesis provides information on how the image quality is affected by different scan parameters on the MARS spectral CT using a Medipix3 silicon quad detector. In particular, it explores how different numbers of projections, exposure time products (mAs), and peak tube voltages (kVp) with different threshold energies (kV) effect the image noise, image resolution and image uniformity, respectively. This provides a set of guidelines for future work using the MARS scanner to obtain images of optimal quality. This thesis also determines that the new image reconstruction software mART developed by Niels de Ruiter, is a suitable replacement for the reconstruction software OctopusCT that is currently being used by the MARS team. Using mART reduces the scan times and dose delivered by the MARS spectral CT.

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Book chapters on the topic "Medipix3"

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Frallicciardi, P. M., G. Mettivier, M. C. Montesi, and P. Russo. "An Image Quality Study of Medipix2 Single Photon Counting Detector Based on Two Kinds of Flat Field Corrections for Breast Computed Tomography Application." In IFMBE Proceedings, 685–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03879-2_192.

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DAMMER, JIRI, VIT SOPKO, JAN JAKUBEK, FRANTISEK WEYDA, JIRI BENES, and JULIAN ZAHOROVSKY. "MICRO-RADIOGRAPHY OF LIVING BIOLOGICAL ORGANISMS WITH MEDIPIX2 DETECTOR AND APPLICATION OF VARIOUS CONTRAST AGENTS." In Astroparticle, Particle, Space Physics, Radiation Interaction, Detectors and Medical Physics Applications, 559–63. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814405072_0082.

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Conference papers on the topic "Medipix3"

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Gloter, Alexandre. "Electron energy-loss spectroscopy using MerlinEM - Medipix3." In European Microscopy Congress 2020. Royal Microscopical Society, 2021. http://dx.doi.org/10.22443/rms.emc2020.1384.

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Tartoni, N., I. C. Horswell, J. Marchal, E. N. Gimenez, R. D. Fearn, R. G. van Silfhout, R. Garrett, I. Gentle, K. Nugent, and S. Wilkins. "Medipix3 array high performance read-out board for synchrotron research." In SRI 2009, 10TH INTERNATIONAL CONFERENCE ON RADIATION INSTRUMENTATION. AIP, 2010. http://dx.doi.org/10.1063/1.3463348.

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Durst, Jurgen, Peter Bartl, Bjorn Kreisler, Thilo Michel, and Gisela Anton. "Monte Carlo simulation of pixelated photon counting X-ray detectors like the Medipix2 and the Medipix3 using high-Z sensor materials." In 2008 IEEE Nuclear Science Symposium and Medical Imaging conference (2008 NSS/MIC). IEEE, 2008. http://dx.doi.org/10.1109/nssmic.2008.4774361.

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Wong, W., R. Ballabriga, M. Campbell, X. Llopart, L. Tlustos, Carlos Granja, Claude Leroy, and Ivan Stekl. "Counter Architectures for a Single Photon-Counting Pixel Detector such as Medipix3." In Nuclear Physics Medthods and Accelerators in Biology and Medicine. AIP, 2007. http://dx.doi.org/10.1063/1.2825808.

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Ronaldson, J. P., A. P. Butler, N. G. Anderson, R. Zainon, and P. H. Butler. "The performance of MARS-CT using Medipix3 for spectral imaging of soft-tissue." In 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2011). IEEE, 2011. http://dx.doi.org/10.1109/nssmic.2011.6153761.

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Chumacero, E. Miguel, B. De Celis Alonso, M. I. Martínez Hernández, G. Vargas, F. Moreno Barbosa, and E. Moreno Barbosa. "Response of a hybrid pixel detector (MEDIPIX3) to different radiation sources for medical applications." In XIII MEXICAN SYMPOSIUM ON MEDICAL PHYSICS. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4901361.

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Walsh, M. F., R. M. N. Doesburg, J. L. Mohr, R. Ballabriga, A. P. H. Butler, and P. H. Butler. "Improving and characterising the threshold equalisation process for multi-chip Medipix3 cameras in Single Pixel Mode." In 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (2011 NSS/MIC). IEEE, 2011. http://dx.doi.org/10.1109/nssmic.2011.6154667.

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Ballabriga, R., M. Campbell, E. H. M. Heijne, X. Llopart, and L. Tlustos. "The Medipix3 Prototype, a Pixel Readout Chip Working in Single Photon Counting Mode with Improved Spectrometric Performance." In 2006 IEEE Nuclear Science Symposium Conference Record. IEEE, 2006. http://dx.doi.org/10.1109/nssmic.2006.353767.

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Gimenez, E. N., R. Ballabriga, M. Campbell, I. Dolbnya, I. Horswell, Xavier Llopart, J. Marchal, K. J. S. Sawhney, N. Tartoni, and D. Turecek. "Evaluation of the radiation hardness and Charge Summing Mode of a Medipix3-based detector with synchrotron radiation." In 2010 IEEE Nuclear Science Symposium and Medical Imaging Conference (2010 NSS/MIC). IEEE, 2010. http://dx.doi.org/10.1109/nssmic.2010.5874120.

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Tartoni, Nicola, G. Dennis, P. Gibbons, E. Gimenez, I. Horswell, J. Marchal, U. Pedersen, et al. "Excalibur: A three million pixels photon counting area detector for coherent diffraction imaging based on the Medipix3 ASIC." In 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference (2012 NSS/MIC). IEEE, 2012. http://dx.doi.org/10.1109/nssmic.2012.6551164.

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