Relevant bibliographies by topics / Parallell imaging

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Parallell imaging'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Parallell imaging"

1

Ozaki, Isamu, and Isao Hashimoto. "Human Tonotopic Maps and their Rapid Task-Related Changes Studied by Magnetic Source Imaging." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 34, no. 2 (2007): 146–53. http://dx.doi.org/10.1017/s0317167100005965.

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A brief review of previous studies is presented on tonotopic organization of primary auditory cortex (AI) in humans. Based on the place theory for pitch perception, in which place information from the cochlea is used to derive pitch, a well-organized layout of tonotopic map is likely in human AI. The conventional view of tonotopy in human AI is a layout inwhich the medial-to-lateral portion of Heschl's gyrus represents high-to-low frequency tones. However, we have shown that the equivalent current dipole (BCD) in auditory evoked magnetic fields in the rising phase of N100m response dynamically
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Mengxuan Lv, Mengxuan Lv, Bo Dai Bo Dai, Songchao Yin Songchao Yin, Dawei Zhang Dawei Zhang, and and Xu Wang and Xu Wang. "Power efficiency of time-stretch imaging system by using parallel interleaving detection." Chinese Optics Letters 14, no. 10 (2016): 101103–7. http://dx.doi.org/10.3788/col201614.101103.

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Bammer, Roland. "Parallel Imaging." Topics in Magnetic Resonance Imaging 15, no. 3 (2004): 127–28. http://dx.doi.org/10.1097/01.rmr.0000138999.18556.09.

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Bammer, Roland. "Parallel Imaging." Topics in Magnetic Resonance Imaging 15, no. 4 (2004): 221. http://dx.doi.org/10.1097/01.rmr.0000145557.94494.28.

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Qiu, Xiaodong, Dongkai Zhang, Tianlong Ma, et al. "Parallel Ghost Imaging." Advanced Quantum Technologies 3, no. 10 (2020): 2000073. http://dx.doi.org/10.1002/qute.202000073.

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Deshmane, Anagha, Vikas Gulani, Mark A. Griswold, and Nicole Seiberlich. "Parallel MR imaging." Journal of Magnetic Resonance Imaging 36, no. 1 (2012): 55–72. http://dx.doi.org/10.1002/jmri.23639.

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Francavilla, Matteo Alessandro, Stamatios Lefkimmiatis, Jorge F. Villena, and Athanasios G. Polimeridis. "Maxwell parallel imaging." Magnetic Resonance in Medicine 86, no. 3 (2021): 1573–85. http://dx.doi.org/10.1002/mrm.28718.

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Katscher, Ulrich, and Peter Börnert. "Parallel magnetic resonance imaging." Neurotherapeutics 4, no. 3 (2007): 499–510. http://dx.doi.org/10.1016/j.nurt.2007.04.011.

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Miller, G. "Massively Parallel Brain Imaging." Science 326, no. 5951 (2009): 390. http://dx.doi.org/10.1126/science.326_390.

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Vogel, Patrick, Thomas Kampf, Stefan Herz, Martin A. Rückert, Thorsten A. Bley, and Volker C. Behr. "Parallel magnetic particle imaging." Review of Scientific Instruments 91, no. 4 (2020): 045117. http://dx.doi.org/10.1063/1.5126108.

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Dissertations / Theses on the topic "Parallell imaging"

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Herterich, Rebecka, and Anna Sumarokova. "Coil Sensitivity Estimation and Intensity Normalisation for Magnetic Resonance Imaging." Thesis, KTH, Medicinteknik och hälsosystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263149.

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The quest for improved efficiency in magnetic resonance imaging has motivated the development of strategies like parallel imaging where arrays of multiple receiver coils are operated simultaneously in parallel. The objective of this project was to find an estimation of phased-array coil sensitivity profiles of magnetic resonance images of the human body. These sensitivity maps can then be used to perform an intensity inhomogeneity correction of the images. Through investigative work in Matlab, a script was developed that uses data embedded in raw data from a magnetic resonance scan, to generat
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Spence, Dan Kenrick. "Array combination for parallel imaging in Magnetic Resonance Imaging." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5944.

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In Magnetic Resonance Imaging, the time required to generate an image is proportional to the number of steps used to encode the spatial information. In rapid imaging, an array of coil elements and receivers are used to reduce the number of encoding steps required to generate an image. This is done using knowledge of the spatial sensitivity of the array and receiver channels. Recently, these arrays have begun to include a large number of coil elements. Ideally, each coil element would have its own receiver channel to acquire the image data. In practice, this is not always possible due to econom
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Brown, David Gerald. "Instrumentation for parallel magnetic resonance imaging." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4784.

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Parallel magnetic resonance (MR) imaging may be used to increase either the throughput or the speed of the MR imaging experiment. As such, parallel imaging may be accomplished either through a "parallelization" of the MR experiment, or by the use of arrays of sensors. In parallelization, multiple MR scanners (or multiple sensors) are used to collect images from different samples simultaneously. This allows for an increase in the throughput, not the inherent speed, of the MR experiment. Parallel imaging with arrays of sensor coils, on the other hand, makes use of the spatial localization proper
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Qu, Peng. "Advances in parallel imaging reconstruction techniques." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36898582.

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Qu, Peng, and 瞿蓬. "Advances in parallel imaging reconstruction techniques." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36898582.

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Kim, Wan. "Study of parallel MR imaging techniques." Thesis, State University of New York at Buffalo, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1594739.

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<p> In MRI, it is more desirable to scan less data as possible because it reduces MRI scanning time. We want to get a clear image by reconstructing the signals we acquire from the MRI machine. Special scanning or sampling techniques are needed to overcome this issue based on various mathematical methods. </p><p> We present an improved random sampling pattern for SAKE (simultaneous autocalibrating and k-space estimation) reconstruction and an iterative GRAPPA reconstruction using Wiener filter. </p><p> In our iterative method using Wiener filter, in contrast to the conventional GRAPPA wher
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Rane, Swati Dnyandeo. "Parallel magnetic resonance imaging: characterization and comparison." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2578.

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Magnetic Resonance Imaging (MRI) is now increasingly being used for fast imaging applications such as real-time cardiac imaging, functional brain imaging, contrast enhanced MRI, etc. Imaging speed in MRI is mainly limited by different imaging parameters selected by the pulse sequences, the subject being imaged and the RF hardware system in operation. New pulse sequences have been developed in order to decrease the imaging time by a faster k-space scan. However, they may not be fast enough to facilitate imaging in real time. Parallel MRI (pMRI), a technique initially used for improving image SN
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Gol, Gungor Derya. "Subspace Techniques for Parallel Magnetic Resonance Imaging." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406301655.

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Steeden, Jennifer Anne. "Rapid phase-contrast magnetic resonance imaging using spiral trajectories and parallel imaging." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1306873/.

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Phase contrast (PC) MRI is a proven method of measuring blood flow in the clinical environment. Traditionally, PCMR data is acquired using cardiac gated Cartesian sequences. However, these sequences are time consuming and difficult to perform in patients with irregular heart rates. The work of my thesis covers three alternative PC sequences, all using undersampled spiral sequences with SENSE reconstruction algorithms. The first piece of work investigates real-time spiral PCMR. The spiral flow sequence was validated at rest by comparing stroke volumes in the aorta of healthy volunteers, against
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Bjåstad, Tore Grüner. "High frame rate ultrasound imaging using parallel beamforming." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for sirkulasjon og bildediagnostikk, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-5298.

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The human heart contracts and relaxes approximately once each second. This is a complex process where different parts of the cardiac tissue contract and relax at different times and at different rates. The accurate evaluation of this deformation with ultrasound requires the use of a high frame rate. The frame rate of a conventional ultrasound image is limited by the round trip propagation time of the sound pulse along each of the scan lines covering the imaged object. A common technique to increase the frame rate is multiple line acquisition, MLA. Using this technique, several scan lines are a
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Books on the topic "Parallell imaging"

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Reiser, Maximilian, Stefan O. Schonberg, and O. Dietrich. Parallel imaging in clinical MR applications. Springer, 2011.

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Schoenberg, Stefan O., Olaf Dietrich, and Maximilian F. Reiser, eds. Parallel Imaging in Clinical MR Applications. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-68879-2.

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Westermann, Birgit. Parallel volume rendering for image-guided surgery. Shaker Verlag, 1998.

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Chen, Zhong, Jianguo Liu, and Mingyue Ding. MIPPR 2011: Parallel processing of images and optimization and medical imaging processing. Edited by Hua zhong gong xue yuan, National Key Laboratory of Science and Technology on Multi-spectral Information Processing, Guilin dian zi ke ji da xue, SPIE (Society), and International Symposium on Multispectral Image Processing and Pattern Recognition (7th : 2011 : Guilin, China). SPIE, 2011.

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International, Symposium on Multispectral Image Processing and Pattern Recognition (5th 2007 Wuhan China). MIPPR 2007: Medical imaging, parallel processing of images, and optimization techniques : 15-17 November 2007, Wuhan, China. SPIE, 2007.

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Owens, John D. Parallel processing for imaging applications: 24-25 January 2011, San Francisco, California, United States. SPIE, 2011.

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1973-, Liu Jianguo, Hua zhong gong xue yuan, National Laboratory for Multi-spectral Information Processing Technologies, and SPIE (Society), eds. MIPPR 2009: Medical imaging, parallel processing of images, and optimization techniques : 30 October-1 November 2009, Yichang, China. SPIE, 2009.

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International Symposium on Multispectral Image Processing and Pattern Recognition (6th 2009 Yichang Shi, China). MIPPR 2009: Medical imaging, parallel processing of images, and optimization techniques : 30 October-1 November 2009, Yichang, China. Edited by Liu Jianguo 1973-, Hua zhong gong xue yuan, National Laboratory for Multi-spectral Information Processing Technologies, and SPIE (Society). SPIE, 2009.

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Haynor, David R., and Sébastien Ourselin. Medical imaging 2012: Image processing : 6-9 February 2012, San Diego, California, United States. Edited by SPIE (Society) and Agilent Technologies. SPIE, 2012.

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Egiazarian, K. Image processing: Algorithms and systems X ; and, Parallel processing for imaging applications II : 23-25 January 2012, Burlingame, California, United States. Edited by IS & T--the Society for Imaging Science and Technology, SPIE (Society), and Electronic Imaging Science and Technology Symposium (2012 : Burlingame, Calif.). SPIE, 2012.

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Book chapters on the topic "Parallell imaging"

1

Pruessmann, Klaas P. "Parallel Imaging." In How does MRI work? Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-07805-1_9.

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Zuurbier, Ria. "Parallel imaging." In Magnetic Resonance Imaging. Bohn Stafleu van Loghum, 2017. http://dx.doi.org/10.1007/978-90-368-1934-3_13.

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Seiberlich, Nicole, and Mark Griswold. "Parallel Imaging in Angiography." In Magnetic Resonance Angiography. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-1686-0_14.

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Awatsuji, Yasuhiro. "Parallel Phase-Shifting Digital Holography." In Multi-Dimensional Imaging. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118705766.ch1.

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Kline, R., C. Sullivan, R. B. Mignogna, and P. P. Delsanto. "A Parallel Processing Algorithm for Acoustic Tomography." In Acoustical Imaging. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4419-8772-3_91.

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Parker, Greg. "Parallel Imaging with an Array." In The Patrick Moore Practical Astronomy Series. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46316-2_10.

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Michaely, Henrik J., and Niels Oesingmann. "Imaging of Renal Perfusion." In Parallel Imaging in Clinical MR Applications. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-68879-2_39.

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Tonry, John L., Barry Burke, Gerald Luppino, and Nicholas Kaiser. "The Orthogonal Parallel Imaging Transfer Camera." In Scientific Detectors for Astronomy. Springer Netherlands, 2004. http://dx.doi.org/10.1007/1-4020-2527-0_47.

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Weber, Roger, Klemens Böhm, and Hans-Jörg Schek. "Parallel NN-Search for Large Multimedia Repositories." In Computational Imaging and Vision. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9664-0_15.

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Nowinski, Wieslaw L. "A SIMD architecture for medical imaging." In Parallel Processing: CONPAR 92—VAPP V. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55895-0_412.

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Conference papers on the topic "Parallell imaging"

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Sankaranarayanan, Aswin C., and Ashok Veeraraghavan. "Parallel Compressive Imaging." In Computational Optical Sensing and Imaging. OSA, 2015. http://dx.doi.org/10.1364/cosi.2015.cth3e.4.

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Sukharev, Jeffrey, Xiaoqiang Zheng, and Alex Pang. "Tracing parallel vectors." In Electronic Imaging 2006, edited by Robert F. Erbacher, Jonathan C. Roberts, Matti T. Gröhn, and Katy Börner. SPIE, 2006. http://dx.doi.org/10.1117/12.655431.

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Kang, Henry R. "Parallel error diffusion." In Electronic Imaging 2002, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2001. http://dx.doi.org/10.1117/12.453007.

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Rosenberg, Robert O., Marco O. Lanzagorta, Almadena Chtchelkanova, and Alexei Khokhlov. "Parallel visualization of large data sets." In Electronic Imaging, edited by Robert F. Erbacher, Philip C. Chen, Jonathan C. Roberts, and Craig M. Wittenbrink. SPIE, 2000. http://dx.doi.org/10.1117/12.378889.

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Metaxas, Panagiotis T. "Optimal parallel error diffusion dithering." In Electronic Imaging '99, edited by Giordano B. Beretta and Reiner Eschbach. SPIE, 1998. http://dx.doi.org/10.1117/12.334593.

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Mukozaka, Naohisa, Haruyoshi Toyoda, Seiichiro Mizuno, Ming H. Wu, Yoshihiro Nakabo, and Masatoshi Ishikawa. "Column parallel vision system: CPV." In Electronic Imaging 2002, edited by Morley M. Blouke, John Canosa, and Nitin Sampat. SPIE, 2002. http://dx.doi.org/10.1117/12.463438.

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Miyati, Tosiaki, Hiroshi Imai, Akio Ogura, Tsukasa Doi, Toshio Tsuchihashi, and Yoshio Machida. "Novel SNR determination method in parallel MRI." In Medical Imaging, edited by Michael J. Flynn and Jiang Hsieh. SPIE, 2006. http://dx.doi.org/10.1117/12.653482.

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Korti, Amel, and Abdelhafid Bessaid. "Wavelet regularization in parallel imaging." In 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). IEEE, 2017. http://dx.doi.org/10.1109/atsip.2017.8075526.

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Ahmed, Haitham M., Refaat E. Gabr, Abou-Bakr M. Youssef, and Yasser M. Kadah. "Optimizing kernel size in generalized auto-calibrating partially parallel acquisition in parallel magnetic resonance imaging." In SPIE Medical Imaging. SPIE, 2010. http://dx.doi.org/10.1117/12.844597.

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Bittner, U. "Fast Image Processing On Parallel Hardware." In Medical Imaging II, edited by Roger H. Schneider and Samuel J. Dwyer III. SPIE, 1988. http://dx.doi.org/10.1117/12.968684.

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Reports on the topic "Parallell imaging"

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Yanasak, Nathan, Geoff Clarke, R. Jason Stafford, et al. Parallel Imaging in MRI: Technology, Applications, and Quality Control. AAPM, 2015. http://dx.doi.org/10.37206/159.

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Just, Marcel A. Parallel Supercomputing in Cognitive Brain Imaging Other Massive 3-D Dataspaces. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada374854.

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