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Journal articles on the topic 'Virtual imaging'

Author: Grafiati
Published: 10 March 2023

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1

Kay, C. L. "Virtual small bowel imaging." Imaging 11, no. 3 (September 1999): 155–60. http://dx.doi.org/10.1259/img.11.3.110155.

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Bretaudeau, M. L., J. L. Gailly, G. Moris, E. Stefani, and J. Knoplioch. "Virtual imaging: technical elements." RBM-News 19, no. 5 (October 1997): 128–33. http://dx.doi.org/10.1016/s0222-0776(97)89497-7.

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3

Nakata, Norio, Yukio Miyamoto, Fumio Tsujimoto, Junta Harada, Simpei Tada, and Kunihiko Fukuda. "Ultrasound virtual endoscopic imaging." Seminars in Ultrasound, CT and MRI 22, no. 1 (February 2001): 78–84. http://dx.doi.org/10.1016/s0887-2171(01)90020-4.

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4

Paquerault, Sophie. "Breast Imaging Going Virtual." Academic Radiology 18, no. 5 (May 2011): 533–35. http://dx.doi.org/10.1016/j.acra.2011.02.010.

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Huan Deng, Huan Deng, Qionghua Wang Qionghua Wang, Dahai Li Dahai Li, Chenggao Luo Chenggao Luo, and Chaochao Ji Chaochao Ji. "1D integral imaging based on parallax images' virtual reconstruction." Chinese Optics Letters 11, no. 4 (2013): 041101–41103. http://dx.doi.org/10.3788/col201311.041101.

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6

Wapenaar, Kees, Jan Thorbecke, Joost van der Neut, Filippo Broggini, Evert Slob, and Roel Snieder. "Marchenko imaging." GEOPHYSICS 79, no. 3 (May 1, 2014): WA39—WA57. http://dx.doi.org/10.1190/geo2013-0302.1.

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Traditionally, the Marchenko equation forms a basis for 1D inverse scattering problems. A 3D extension of the Marchenko equation enables the retrieval of the Green’s response to a virtual source in the subsurface from reflection measurements at the earth’s surface. This constitutes an important step beyond seismic interferometry. Whereas seismic interferometry requires a receiver at the position of the virtual source, for the Marchenko scheme it suffices to have sources and receivers at the surface only. The underlying assumptions are that the medium is lossless and that an estimate of the direct arrivals of the Green’s function is available. The Green’s function retrieved with the 3D Marchenko scheme contains accurate internal multiples of the inhomogeneous subsurface. Using source-receiver reciprocity, the retrieved Green’s function can be interpreted as the response to sources at the surface, observed by a virtual receiver in the subsurface. By decomposing the 3D Marchenko equation, the response at the virtual receiver can be decomposed into a downgoing field and an upgoing field. By deconvolving the retrieved upgoing field with the downgoing field, a reflection response is obtained, with virtual sources and virtual receivers in the subsurface. This redatumed reflection response is free of spurious events related to internal multiples in the overburden. The redatumed reflection response forms the basis for obtaining an image of a target zone. An important feature is that spurious reflections in the target zone are suppressed, without the need to resolve first the reflection properties of the overburden.
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7

Ferralli, Michael W. "Virtual imaging multiple transducer system." Journal of the Acoustical Society of America 103, no. 4 (April 1998): 1697. http://dx.doi.org/10.1121/1.421313.

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8

Galvin, Jeffrey R., Michael P. DʼAlessandro, William E. Erkonen, Wilbur L. Smith, Georges Y. El-Khoury, and James N. Weinstein. "Imaging Corner The Virtual Hospital." Spine 20, no. 15 (August 1995): 1735–38. http://dx.doi.org/10.1097/00007632-199508000-00017.

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9

JOHNSON, KATE. "Virtual Colorectal Imaging: New Era?" Internal Medicine News 39, no. 23 (December 2006): 1–5. http://dx.doi.org/10.1016/s1097-8690(06)74558-9.

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10

Nomura, Takakiyo, Tetsu Niwa, Soji Ozawa, Yutaka Imai, and Jun Hashimoto. "Visibility of bronchial arteries using virtual and advanced virtual monoenergetic imaging." Acta Radiologica 61, no. 12 (May 19, 2020): 1618–27. http://dx.doi.org/10.1177/0284185120923992.

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Background The utility of virtual monoenergetic imaging (VMI) for fine arteries has not been well clarified. Purpose To assess bronchial artery visualization using VMI and noise-optimized advanced VMI (VMI+). Material and Methods Eighty-seven patients with esophageal cancer underwent computed tomography (CT) using a third-generation dual-source system before surgery. Tube voltages were set to 90 kVp and 150 kVp, respectively. Images were reconstructed using VMI and VMI+ with energy levels of 40–120 keV (in 10-keV increments); composite images equivalent to CT images at 105 kVp were also generated. The CT attenuation value and contrast-to-noise ratio (CNR) of bronchial arteries using VMI and VMI+ were compared with those obtained using composite imaging. Two radiologists subjectively analyzed bronchial artery visualization with reference to the composite image. Results CT attenuation values for bronchial arteries using VMI at 40–60 keV and VMI+ at 40 keV and 50 keV were significantly higher than those obtained using composite imaging ( P < 0.05). CNR using VMI at 40–60 keV was significantly higher than that obtained using composite imaging ( P < 0.05), whereas no differences were noted for values obtained using composite imaging between VMI+ at 40 keV and 50 keV. In the subjective analysis, VMI at 40 keV and 50 keV yielded significantly better visibility of bronchial arteries than VMI+ ( P < 0.05). Conclusion VMI and VMI+ at low voltages (40–50 keV) may be useful for bronchial artery visualization. VMI+ may be less effective for fine vessels as bronchial artery visualization.
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11

Wildermuth, Simon, and Jörg F. Debatin. "VIRTUAL ENDOSCOPY IN ABDOMINAL MR IMAGING." Magnetic Resonance Imaging Clinics of North America 7, no. 2 (May 1999): 349–64. http://dx.doi.org/10.1016/s1064-9689(21)00027-1.

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12

Kotani, Toshiaki, Shigeyuki Nagaya, Masaru Sonoda, Tsutomu Akazawa, Jose Miguel T. Lumawig, Tetsuharu Nemoto, Takana Koshi, Koshiro Kamiya, Naoya Hirosawa, and Shohei Minami. "Virtual Endoscopic Imaging of the Spine." Spine 37, no. 12 (May 2012): E752—E756. http://dx.doi.org/10.1097/brs.0b013e318255d2f5.

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13

Gammer, Christoph, V. Burak Ozdol, Christian H. Liebscher, and Andrew M. Minor. "Diffraction contrast imaging using virtual apertures." Ultramicroscopy 155 (August 2015): 1–10. http://dx.doi.org/10.1016/j.ultramic.2015.03.015.

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14

Yovel, Yossi, and Yaniv Assaf. "Virtual definition of neuronal tissue by cluster analysis of multi-parametric imaging (virtual-dot-com imaging)." NeuroImage 35, no. 1 (March 2007): 58–69. http://dx.doi.org/10.1016/j.neuroimage.2006.08.055.

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15

Zhang, Yimin D., Xizhong Shen, Ramazan Demirli, and Moeness G. Amin. "Ultrasonic Flaw Imaging via Multipath Exploitation." Advances in Acoustics and Vibration 2012 (August 1, 2012): 1–12. http://dx.doi.org/10.1155/2012/874081.

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We consider ultrasonic imaging for the visualization of flaws in a material. Ultrasonic imaging is a powerful nondestructive testing (NDT) tool which assesses material conditions via the detection, localization, and classification of flaws inside a structure. We utilize reflections of ultrasonic signals which occur when encountering different media and interior boundaries. These reflections can be cast as direct paths to the target corresponding to the virtual sensors appearing on the top and bottom side of the target. Some of these virtual sensors constitute a virtual aperture, whereas in others, the aperture changes with the transmitter position. Exploitations of multipath extended virtual array apertures provide enhanced imaging capability beyond the limitation of traditional multisensor approaches. The waveforms observed at the physical as well as the virtual sensors yield additional measurements corresponding to different aspect angles, thus allowing proper multiview imaging of flaws. We derive the wideband point spread functions for dominant multipaths and show that fusion of physical and virtual sensor data improves the flaw perimeter detection and localization performance. The effectiveness of the proposed multipath exploitation approach is demonstrated using real data.
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16

Marquez, Miguel, Hoover Rueda-Chacon, and Henry Arguello. "Compressive Spectral Imaging Via Virtual Side Information." IEEE Transactions on Computational Imaging 7 (2021): 114–23. http://dx.doi.org/10.1109/tci.2021.3052050.

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17

Hyun, Dong-Il, Young-Cheol Park, and Dae Hee Youn. "Enhanced Amplitude Panning for Virtual Source Imaging." Journal of the Institute of Electronics Engineers of Korea 50, no. 3 (March 25, 2013): 139–45. http://dx.doi.org/10.5573/ieek.2013.50.3.139.

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18

Haliloglu, Nuray, and Caglar Uzun. "Virtual colonoscopy: Imaging technique and clinical indications." Türk Radyoloji Dergisi/Turkish Journal of Radiology 35, no. 2 (October 28, 2016): 64–69. http://dx.doi.org/10.5152/turkjradiol.2016.385.

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19

Fenlon, H. M., P. D. Clarke, and J. T. Ferrucci. "Virtual colonoscopy: imaging features with colonoscopic correlation." American Journal of Roentgenology 170, no. 5 (May 1998): 1303–9. http://dx.doi.org/10.2214/ajr.170.5.9574607.

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20

Dodelzon, Katerina, Amy Patel, and Dana Smetherman. "National Virtual Visiting Professorship in Breast Imaging." Journal of the American College of Radiology 19, no. 2 (February 2022): 278–80. http://dx.doi.org/10.1016/j.jacr.2021.11.006.

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21

Gong, Yu, Yue Gang Hu, Guo Rong Song, Cun Fu He, and Bin Wu. "Ultrasonic Imaging System Based on Virtual Instrument." Advanced Materials Research 663 (February 2013): 616–20. http://dx.doi.org/10.4028/www.scientific.net/amr.663.616.

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An imaging system of ultrasonic detection is presented for non-destructive testing (NDT) of complex structures by using virtual instrument technology. The control devices for C-scan as well as for imaging system are designed and manufactured. In the coarse scan mode with the scan step of 1 mm, the system can quickly give an image display of a cross section of 80 mm (L) ×60 mm (D) by one measurement. In the refined scan model, the system can show a refine image of the coin. All experiments on coin, bulk metal, and other forms of specimen verify the efficiency of the proposed method. The experimental results are accurate and reliable.
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22

Dirnhofer, Richard, Christian Jackowski, Peter Vock, Kimberlee Potter, and Michael J. Thali. "VIRTOPSY: Minimally Invasive, Imaging-guided Virtual Autopsy." RadioGraphics 26, no. 5 (September 2006): 1305–33. http://dx.doi.org/10.1148/rg.265065001.

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23

Meles, Giovanni Angelo, Kees Wapenaar, and Jan Thorbecke. "Virtual plane-wave imaging via Marchenko redatuming." Geophysical Journal International 214, no. 1 (April 12, 2018): 508–19. http://dx.doi.org/10.1093/gji/ggy143.

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24

Takeuchi, Takashi, and Philip A. Nelson. "Optimal source distribution for virtual acoustic imaging." Journal of the Acoustical Society of America 108, no. 5 (November 2000): 2561. http://dx.doi.org/10.1121/1.4743510.

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25

Mannerheim, P., and P. A. Nelson. "Virtual Sound Imaging Using Visually Adaptive Loudspeakers." Acta Acustica united with Acustica 94, no. 6 (November 1, 2008): 1024–39. http://dx.doi.org/10.3813/aaa.918118.

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26

Ferretti, G. R., I. Bricault, and M. Coulomb. "Virtual tools for imaging of the thorax." European Respiratory Journal 18, no. 2 (August 1, 2001): 381–92. http://dx.doi.org/10.1183/09031936.01.00217701.

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27

Gunn, Therese. "3. A 3D VIRTUAL MEDICAL IMAGING SUITE." Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare 9, no. 1 (February 2014): 74. http://dx.doi.org/10.1097/01.sih.0000444025.17185.de.

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28

Kempadoo, Roshini. "Imaging historical traces: Virtual Exiles project [2000]." Small Axe: A Caribbean Journal of Criticism 8, no. 1 (March 1, 2004): 235–41. http://dx.doi.org/10.1215/-8-1-235.

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29

Peng, Xiang, Zhiyong Cui, and Tieniu Tan. "Information encryption with virtual-optics imaging system." Optics Communications 212, no. 4-6 (November 2002): 235–45. http://dx.doi.org/10.1016/s0030-4018(02)02003-5.

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30

Cong, Wenxiang, Yan Xi, Paul Fitzgerald, Bruno De Man, and Ge Wang. "Virtual Monoenergetic CT Imaging via Deep Learning." Patterns 1, no. 8 (November 2020): 100128. http://dx.doi.org/10.1016/j.patter.2020.100128.

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31

Anwander, A., R. Schurade, M. Hlawitschka, G. Scheuermann, and T. R. Knösche. "White Matter Imaging with Virtual Klingler Dissection." NeuroImage 47 (July 2009): S105. http://dx.doi.org/10.1016/s1053-8119(09)70916-4.

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32

Rosenkrantz, Andrew B., Jason Sherwin, Chandan P. Prithiani, Dana Ostrow, and Michael P. Recht. "Technology-Assisted Virtual Consultation for Medical Imaging." Journal of the American College of Radiology 13, no. 8 (August 2016): 995–1002. http://dx.doi.org/10.1016/j.jacr.2016.02.029.

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33

Liu, Jie, Ahmad Karfoul, Longyu Jiang, Huazhong Shu, Hervé Saint-Jalmes, and Giulio Gambarota. "ViP-CSI: Virtual Phantom Chemical Shift Imaging." Applied Magnetic Resonance 49, no. 4 (January 20, 2018): 369–80. http://dx.doi.org/10.1007/s00723-018-0981-6.

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34

Weinstein, Ronald S. "Innovations in medical imaging and virtual microscopy." Human Pathology 36, no. 4 (April 2005): 317–19. http://dx.doi.org/10.1016/j.humpath.2005.03.007.

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35

Pinchera, Daniele, Marco Donald Migliore, and Gaetano Panariello. "A Virtual Subarray Architecture for Imaging Radar." IEEE Transactions on Antennas and Propagation 62, no. 10 (October 2014): 5171–79. http://dx.doi.org/10.1109/tap.2014.2346176.

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36

Palmeri, Roberta, Martina Teresa Bevacqua, Lorenzo Crocco, Tommaso Isernia, and Loreto Di Donato. "Microwave Imaging via Distorted Iterated Virtual Experiments." IEEE Transactions on Antennas and Propagation 65, no. 2 (February 2017): 829–38. http://dx.doi.org/10.1109/tap.2016.2633070.

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37

Yan, Haochen, Yunzhao Wu, Yuqi Zhou, Muzhen Xu, Petra Paiè, Cheng Lei, Sheng Yan, and Keisuke Goda. "Virtual optofluidic time-stretch quantitative phase imaging." APL Photonics 5, no. 4 (April 1, 2020): 046103. http://dx.doi.org/10.1063/1.5134125.

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38

Erkol, Hakan, and Mehmet Burcin Unlu. "Virtual source method for diffuse optical imaging." Applied Optics 52, no. 20 (July 9, 2013): 4933. http://dx.doi.org/10.1364/ao.52.004933.

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39

Saint-Jalmes, Hervé, Pierre-Antoine Eliat, Johanne Bezy-Wendling, Alejandro Bordelois, and Giulio Gambarota. "ViP MRI: virtual phantom magnetic resonance imaging." Magnetic Resonance Materials in Physics, Biology and Medicine 27, no. 5 (December 15, 2013): 419–24. http://dx.doi.org/10.1007/s10334-013-0425-0.

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40

Wang, Dongxu, Junzhi Sang, Ruinan Liu, Mengyu Chen, and Xing Ma. "Research on Application of micro assistant combined with PACS based virtual imaging system in teaching imaging internship." Advances in Education, Humanities and Social Science Research 1, no. 3 (February 2, 2023): 251. http://dx.doi.org/10.56028/aehssr.3.1.251.

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Objective: To investigate the effect of micro assistant combined with image storage and transmission system based virtual imaging system in medical imaging internship teaching. Methods: a total of 61 imaging professional students who entered the Department of imaging, the Second Affiliated Hospital of Qiqihar Medical College, from August 1st 2019, were randomly divided into test group and control group in the Department of trial. Results: The students in the test group were significantly better than the students in the control group in attendance examination performance, the difference was statistically significant, in the satisfaction survey of teaching methods, the micro - Assistant combined with PACS based virtual imaging system teaching methods were significantly higher in student satisfaction than the traditional teaching methods. Conclusions: the combination of micro assistant and PACS based virtual imaging system in medical imaging internship teaching can improve students' knowledge of the imaging characteristics of diseases.
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41

Vining, David J. "Virtual colonoscopy." Seminars in Ultrasound, CT and MRI 20, no. 1 (February 1999): 56–60. http://dx.doi.org/10.1016/s0887-2171(99)90007-0.

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42

Laghi, Andrea. "Virtual Colonoscopy." Current Medical Imaging Reviews 1, no. 3 (November 1, 2005): 303–12. http://dx.doi.org/10.2174/157340505774574745.

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43

McLennan, G., E. Namati, J. Ganatra, M. Suter, E. E. O'Brien, K. Lecamwasam, E. J. R. van Beek, and E. A. Hoffman. "Virtual Bronchoscopy." Imaging Decisions MRI 11, no. 1 (March 2007): 10–20. http://dx.doi.org/10.1111/j.1617-0830.2007.00087.x.

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44

Andresen, K. J. "Virtual Colonoscopy." Imaging Decisions MRI 11, no. 1 (March 2007): 21–28. http://dx.doi.org/10.1111/j.1617-0830.2007.00088.x.

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45

Hackländer, Thomas, and Heinrich Mertens. "Virtual MRI." Academic Radiology 12, no. 1 (January 2005): 85–96. http://dx.doi.org/10.1016/j.acra.2004.09.011.

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46

Lu, Biying, Yang Zhao, Xin Sun, and Zhimin Zhou. "Design and Analysis of Ultra-Wideband Split Transmit Virtual Aperture Array for Through-the-Wall Imaging." International Journal of Antennas and Propagation 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/934509.

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The concept of virtual aperture and the point spread function for designing and characterizing ultra-wideband near-field multiple-input multiple-output active imaging array are investigated. Combining the approach of virtual aperture desynthesis with the monostatic-to-bistatic equivalence theorem, a kind of linear UWB MIMO array, the split transmit virtual aperture (STVA) array, was designed for through-the-wall imaging. Given the virtual aperture, the STVA array is the shortest in physical aperture length. The imaging performance of the designed STVA array in the near field is fully analyzed through both numerical and measured data. The designed STVA array has been successfully applied to imaging moving targets inside buildings.
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47

Rymarczyk, Tomasz, Jan Sikora, Przemysław Adamkiewicz, Piotr Bożek, and Michał Gołąbek. "THE CHANCES OF PRECISION ENHANCE FOR ULTRASONIC IMAGING." Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 8, no. 3 (September 25, 2018): 19–24. http://dx.doi.org/10.5604/01.3001.0012.5277.

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The results of ultrasonic imaging with the aid of an algorithm with the virtual rays is presented in this paper. The signal associated with the virtual rays is calculated as an arithmetical mean value of the signals of the rays surrounding the virtual one. Developed algorithm was tested on synthetic free noise data then polluted synthetic data in order to move for the real measurements. Conclusions about the imaging with new algorithm are not obvious. In same cases the significant improvement was achieved but in some not.
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48

Mullen, Michael, Alexander Gutierrez, Naoharu Kobayashi, Jarvis Haupt, and Michael Garwood. "Accelerated imaging with segmented 2D pulses using parallel imaging and virtual coils." Journal of Magnetic Resonance 305 (August 2019): 185–94. http://dx.doi.org/10.1016/j.jmr.2019.07.001.

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49

Sutcliffe, M., M. Weston, P. Charlton, B. Dutton, and K. Donne. "Virtual source aperture imaging for non-destructive testing." Insight - Non-Destructive Testing and Condition Monitoring 54, no. 7 (July 1, 2012): 371–79. http://dx.doi.org/10.1784/insi.2012.54.7.371.

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50

Vesenjak, Matej, Jože Matela, Philippe Young, Rajab Said, and Zoran Ren. "Imaging, virtual reconstruction and computational material tissue) testing." Acta Medico-Biotechnica 2, no. 01 (September 20, 2021): 19–30. http://dx.doi.org/10.18690/actabiomed.10.

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Purpose: Recent advances in professional software and computer hardware allow for reliable computational analyses of new engineering materials as well as biological tissues. Therefore, the purpose of this paper is to describe the procedures allowing detailed reconstruction and virtual testing of such materials. Methods: This paper describes the procedures and techniques for computational reconstruction of specimens, based on three-dimensional (3D) imaging data sets. First, different techniques of acquiring 3D imaging data sets (i.e., computed tomography – CT, magnetic resonance imaging – MRI and ultrasound – US) are introduced. Next the virtual reconstruction procedures for generated material (tissue) scans, based on image recognition, are addressed. For this purpose the up-to-date commercial software package ScanIP was used, allowing for an automatic virtual reconstruction. Results: The reconstructed models can be virtually redesigned and adopted for special requirements or can be discretized (using +ScanFE and +ScanCAD) for further computational analysis, for example to predict their behaviour under quasi-static or dynamic loading conditions. Conclusions: The paper concludes with three practical examples: (i) reconstruction and structural analysis of the proximal femur (alone and with a modelled implant), (ii) reconstruction of the lumbar spine and (iii) reconstruction and structural analysis of an irregular aluminium cellular material. The proposed procedures proved to be sophisticated and effective techniques suitable for a wide spectrum of medical and engineering applications.
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