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Journal articles on the topic '2D/3D'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Гласко, Ю. В. "2D and 3D algorithms of introcontinuation." Numerical Methods and Programming (Vychislitel'nye Metody i Programmirovanie), no. 3 (September 20, 2016): 291–98. http://dx.doi.org/10.26089/nummet.v17r327.

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Рассматривается задача интропродолжения поля с целью локализации источников его аномалий. Предложены математическая модель поля (сводящаяся к задаче Дирихле, в которой в качестве границы области выступает дневная поверхность), а так же новые 2D- и 3D-алгоритмы решения указанной задачи. Алгоритмы локализации особых точек продолженного в нижнюю полуплоскость поля базируются на расчете конечно-разностных аппроксимаций полного нормированного градиента В.М. Березкина (КПНГ). Разработаны два конечно-разностных варианта интропродолжения, сокращающих (в сравнении с рядами Фурье) количество необходимой для работы алгоритма априорной информации. Представлен модельный пример работы методики в площадном (3D) варианте, позволяющий локализовать объекты по наблюденному гравитационному полю. The introcontinuation of a potential field for the localization of sources in the field's anomalies is discussed. A mathematical model of the field is proposed on the basis of the Dirichlet problem with a condition on the day surface. New 2D and 3D algorithms are developed to determine the critical points for the field continued into the lower half-plane. These algorithms are based on a finite-difference approximation of Berezkin's complete normalized gradient and on the determination of its critical points. Two versions of the finite-difference introcontinuation reduce a priori information requiring for the algorithms. A model experiment for the areal version (3D) procedure is considered to illustrate the determination of objects by the observed gravity field.

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2

Boriskevich, A. A., V. K. Erohovets, and V. V. Tkachenko. "3D and 2D/3D holograms model." Optical Memory and Neural Networks 21, no. 4 (October 2012): 242–48. http://dx.doi.org/10.3103/s1060992x12040030.

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3

De Feyter, Steven. "From 2D to 3D." Nature Chemistry 3, no. 1 (December 15, 2010): 14–15. http://dx.doi.org/10.1038/nchem.938.

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4

PARTIK, BERNHARD L., ALFRED STADLER, STEPHAN SCHAMP, ANKE KOLLER, MARTIN VORACEK, GERTRAUD HEINZ, and THOMAS H. HELBICH. "3D Versus 2D Ultrasound." Investigative Radiology 37, no. 9 (September 2002): 489–95. http://dx.doi.org/10.1097/00004424-200209000-00003.

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5

Kim, Gang Yeon, and Seong Min Son. "Realistic 3D model generation of a real product based on 2D-3D registration." Journal of the Korea Academia-Industrial cooperation Society 14, no. 11 (November 30, 2013): 5385–91. http://dx.doi.org/10.5762/kais.2013.14.11.5385.

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6

Caruana, Matthew, and Joseph G. Vella. "3D Facial Reconstruction from 2D Portrait Imagery." Information & Security: An International Journal 47, no. 3 (2020): 328–40. http://dx.doi.org/10.11610/isij.4724.

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7

Trache, Tudor, Stephan Stöbe, Adrienn Tarr, Dietrich Pfeiffer, and Andreas Hagendorff. "The agreement between 3D, standard 2D and triplane 2D speckle tracking: effects of image quality and 3D volume rate." Echo Research and Practice 1, no. 2 (November 2014): 71–83. http://dx.doi.org/10.1530/erp-14-0025.

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Comparison of 3D and 2D speckle tracking performed on standard 2D and triplane 2D datasets of normal and pathological left ventricular (LV) wall-motion patterns with a focus on the effect that 3D volume rate (3DVR), image quality and tracking artifacts have on the agreement between 2D and 3D speckle tracking. 37 patients with normal LV function and 18 patients with ischaemic wall-motion abnormalities underwent 2D and 3D echocardiography, followed by offline speckle tracking measurements. The values of 3D global, regional and segmental strain were compared with the standard 2D and triplane 2D strain values. Correlation analysis with the LV ejection fraction (LVEF) was also performed. The 3D and 2D global strain values correlated good in both normally and abnormally contracting hearts, though systematic differences between the two methods were observed. Of the 3D strain parameters, the area strain showed the best correlation with the LVEF. The numerical agreement of 3D and 2D analyses varied significantly with the volume rate and image quality of the 3D datasets. The highest correlation between 2D and 3D peak systolic strain values was found between 3D area and standard 2D longitudinal strain. Regional wall-motion abnormalities were similarly detected by 2D and 3D speckle tracking. 2DST of triplane datasets showed similar results to those of conventional 2D datasets. 2D and 3D speckle tracking similarly detect normal and pathological wall-motion patterns. Limited image quality has a significant impact on the agreement between 3D and 2D numerical strain values.

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8

Ballantyne, Lauren. "Comparing 2D and 3D Imaging." Journal of Visual Communication in Medicine 34, no. 3 (September 2011): 138–41. http://dx.doi.org/10.3109/17453054.2011.605057.

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9

Sumkin, Jules H. "Integrated 2D and 3D mammography." Lancet Oncology 14, no. 8 (July 2013): e292-e293. http://dx.doi.org/10.1016/s1470-2045(13)70223-7.

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10

Gough, N. R. "Moving in 2D Versus 3D." Science Signaling 3, no. 138 (September 7, 2010): ec274-ec274. http://dx.doi.org/10.1126/scisignal.3138ec274.

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11

Hergel, Jean, and Sylvain Lefebvre. "3D Fabrication of 2D Mechanisms." Computer Graphics Forum 34, no. 2 (May 2015): 229–38. http://dx.doi.org/10.1111/cgf.12555.

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12

Gao, Z. X., E. Osquiguil, M. Maenhoudt, B. Wuyts, S. Libbrecht, and Y. Bruynseraede. "3D-2D dimensional crossover inYBa2Cu3O7films." Physical Review Letters 71, no. 19 (November 8, 1993): 3210–13. http://dx.doi.org/10.1103/physrevlett.71.3210.

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13

Erlandsson, K., and S. E. Strand. "3D reconstruction for 2D PET." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 391, no. 2 (June 1997): 369–74. http://dx.doi.org/10.1016/s0168-9002(97)00321-5.

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14

Khoruzhenko, A. I. "2D- and 3D-cell culture." Biopolymers and Cell 27, no. 1 (January 20, 2011): 17–24. http://dx.doi.org/10.7124/bc.00007d.

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15

Jebara, T., A. Azarbayejani, and A. Pentland. "3D structure from 2D motion." IEEE Signal Processing Magazine 16, no. 3 (May 1999): 66–84. http://dx.doi.org/10.1109/79.768574.

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16

Magsipoc, Earl, Qi Zhao, and Giovanni Grasselli. "2D and 3D Roughness Characterization." Rock Mechanics and Rock Engineering 53, no. 3 (October 10, 2019): 1495–519. http://dx.doi.org/10.1007/s00603-019-01977-4.

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17

Kornél, Klement. "2D and 3D Perspective transformations." Computers & Graphics 14, no. 1 (January 1990): 117–24. http://dx.doi.org/10.1016/0097-8493(90)90015-p.

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18

Schaeben, Helmut, Marcus Apel, K. Gerald v. d. Boogaart, and Uwe Kroner. "GIS 2D, 3D, 4D, nD." Informatik-Spektrum 26, no. 3 (June 2003): 173–79. http://dx.doi.org/10.1007/s00287-003-0303-7.

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19

Käläntär, K. "Switching directional BLUs for full-resolution auto-stereoscopic 3D/2D and 2D/3D LCDs." Journal of the Society for Information Display 25, no. 4 (April 2017): 266–76. http://dx.doi.org/10.1002/jsid.555.

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20

Dmitriev, S. V. "Gap discrete breathers in 2D and 3D crystals." Letters on Materials 1, no. 2 (2011): 78–83. http://dx.doi.org/10.22226/2410-3535-2011-2-78-83.

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21

Fisichella, V. A., F. Jäderling, S. Horvath, P. O. Stotzer, A. Kilander, and M. Hellström. "Primary three-dimensional analysis with perspective-filet view versus primary two-dimensional analysis: Evaluation of lesion detection by inexperienced readers at computed tomographic colonography in symptomatic patients." Acta Radiologica 50, no. 3 (April 2009): 244–55. http://dx.doi.org/10.1080/02841850802714797.

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Background: “Perspective-filet view” is a novel three-dimensional (3D) viewing technique for computed tomography colonography (CTC). Studies with experienced readers have shown a sensitivity for perspective-filet view similar to that of 2D or 3D endoluminal fly-through in detection of colorectal lesions. It is not known whether perspective-filet view, compared to axial images, improves lesion detection by inexperienced readers. Purpose: To compare primary 3D analysis using perspective-filet view (3D Filet) with primary 2D analysis, as used by inexperienced CTC readers. Secondary aims were to compare lesion detection by 3D Filet when used by experienced and inexperienced readers, and to evaluate the effect of combined 3D Filet + 2D analysis. Material and Methods: Fifty symptomatic patients were prospectively enrolled. An experienced reader performed 3D Filet analysis followed by complete 2D analysis (3D Filet + 2D), before colonoscopy with segmental unblinding. Two inexperienced readers (readers 2 and 3), blinded to CTC and colonoscopy findings, retrospectively performed 3D Filet analysis and, after 5 weeks, 2D analysis. True positives ≥6 mm detected by the inexperienced readers with 3D Filet and/or 2D were combined to obtain 3D Filet + 2D. Results: Colonoscopy revealed 116 lesions: 16 lesions ≥10 mm, 19 lesions 6–9 mm, and 81 lesions ≤5 mm. For the experienced reader, sensitivities for lesions ≥6 mm with 3D Filet and 3D Filet + 2D were 77% and 83%, respectively. For the inexperienced readers, sensitivities for lesions ≥6 mm with 3D Filet and 2D were 51% and 57% (reader 2) and 40% and 43% (reader 3), respectively. There was no significant difference between 3D Filet and 2D regarding sensitivity and reading time. For lesions ≥6 mm, 3D Filet + 2D improved the sensitivity of reader 2 to 63% and of reader 3 to 51%. Conclusion: Lesion detection by inexperienced readers using perspective-filet view is comparable to that obtained by 2D. Lesion detection improves by combining 3D Filet + 2D, but not to the level of an experienced reader.

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22

Wang, Yong Sheng. "Fast 3D Human Face Modeling Method Based on Multiple View 2D Images." Applied Mechanics and Materials 273 (January 2013): 796–99. http://dx.doi.org/10.4028/www.scientific.net/amm.273.796.

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This paper presents a novel approach to model 3D human face from multiple view 2D images in a fast mode. Our proposed method mainly includes three steps: 1) Face Recognition from 2D images, 2) Converting 2D images to 3D images, 3) Modeling 3D human face. To extract visual features of both 2D and 3D images, visual features adopted in 3D are described by Point Signature, and visual features utilized in 2D is represented by Gabor filter responses. Afterwards, 3D model is obtained by combining multiple view 2D images through calculating projections vector and translation vector. Experimental results show that our method can model 3D human face with high accuracy and efficiency.

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23

Mao, Xiaoyang, Tosiyasu Kunii, Issei Fujishiro, and Tsukasa Noma. "Hierarchical Representations of 2D/3D Gray-Scale Images and Their 2D/3D Two-Way Conversion." IEEE Computer Graphics and Applications 7, no. 12 (December 1987): 37–44. http://dx.doi.org/10.1109/mcg.1987.276937.

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24

Rabie, Tamer. "Rapid 2D-3D Conversion for Low-Cost 3D Television." International Journal of Computer Applications 102, no. 6 (September 18, 2014): 1–7. http://dx.doi.org/10.5120/17816-8751.

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25

Bäck, A. "Quasi 3D dosimetry (EPID, conventional 2D/3D detector matrices)." Journal of Physics: Conference Series 573 (January 12, 2015): 012012. http://dx.doi.org/10.1088/1742-6596/573/1/012012.

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26

van Manen, Teunis, Shahram Janbaz, and Amir A. Zadpoor. "Programming 2D/3D shape-shifting with hobbyist 3D printers." Materials Horizons 4, no. 6 (2017): 1064–69. http://dx.doi.org/10.1039/c7mh00269f.

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27

Choi, Tae-Jun, and Hee-Man Lee. "An Algorithim for Converting 2D Face Image into 3D Model." Journal of the Korea Society of Computer and Information 20, no. 4 (April 30, 2015): 41–48. http://dx.doi.org/10.9708/jksci.2015.20.4.041.

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28

Watanabe, Megumi, Yosuke Ida, Masato Furuhashi, Yuri Tsugeno, Hiroshi Ohguro, and Fumihito Hikage. "Screening of the Drug-Induced Effects of Prostaglandin EP2 and FP Agonists on 3D Cultures of Dexamethasone-Treated Human Trabecular Meshwork Cells." Biomedicines 9, no. 8 (July 31, 2021): 930. http://dx.doi.org/10.3390/biomedicines9080930.

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The objective of the current study was to perform a screening of the drug-induced effects of the prostaglandin F2α (PGF2α) and EP2 agonist, omidenepag (OMD), using two- and three-dimensional (2D and 3D) cultures of dexamethasone (DEX)-treated human trabecular meshwork (HTM) cells. The drug-induced effects on 2D monolayers were characterized by measuring the transendothelial electrical resistance (TEER) and fluorescein isothiocyanate (FITC)–dextran permeability, the physical properties of 3D spheroids, and the gene expression of extracellular matrix (ECM) molecules, including collagen (COL) 1, 4 and 6, and fibronectin (FN), α smooth muscle actin (αSMA), a tissue inhibitor of metalloproteinase (TIMP) 1–4, matrix metalloproteinase (MMP) 2, 9 and 14 and endoplasmic reticulum (ER) stress-related factors. DEX induced a significant increase in TEER values and a decrease in FITC–dextran permeability, respectively, in the 2D HTM monolayers, and these effects were substantially inhibited by PGF2α and OMD. Similarly, DEX also caused decreased sizes and an increased stiffness in the 3D HTM spheroids, but PGF2α or OMD had no effects on the stiffness of the spheroids. Upon exposure to DEX, the following changes were observed: the upregulation of COL4 (2D), αSMA (2D), and TIMP4 (2D and 3D) and the downregulation of TIMP1 and 2 (3D), MMP2 and 14 (3D), inositol-requiring enzyme 1 (IRE1), activating transcription factor 6 (ATF6) (2D), and glucose regulator protein (GRP)78 (3D). In the presence of PGF2α or OMD, the downregulation of COL4 (2D), FN (3D), αSMA (2D), TIMP3 (3D), MMP9 (3D) and the CCAAT/enhancer-binding protein homologous protein (CHOP) (2D), and the upregulation of TIMP4 (2D and 3D), MMP2, 9 and 14 (2D), respectively, were observed. The findings presented herein suggest that 2D and 3D cell cultures can be useful in screening for the drug-induced effects of PGF2α and OMD toward DEX-treated HTM cells.

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Qin, Ling, Mingdao Zhang, Qingxiang Yang, Yizhi Li, and Hegen Zheng. "Three 2D/2D → 2D or 3D Coordination Polymers: Parallel Stacked, Interpenetration, and Polycatenated." Crystal Growth & Design 13, no. 11 (October 21, 2013): 5045–49. http://dx.doi.org/10.1021/cg401207s.

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30

Bokhov, O. S., and P. V. Afanas'ev. "Using Electrospinning Technology for Printing 2D- and 3D-Nanostructures." Nano- i Mikrosistemnaya Tehnika 19, no. 8 (August 17, 2017): 475–80. http://dx.doi.org/10.17587/nmst.19.475-480.

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31

Hättenschwiler, Nicole, Marcia Mendes, and Adrian Schwaninger. "Detecting Bombs in X-Ray Images of Hold Baggage: 2D Versus 3D Imaging." Human Factors: The Journal of the Human Factors and Ergonomics Society 61, no. 2 (September 24, 2018): 305–21. http://dx.doi.org/10.1177/0018720818799215.

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Objective: This study compared the visual inspection performance of airport security officers (screeners) when screening hold baggage with state-of-the-art 3D versus older 2D imaging. Background: 3D imaging based on computer tomography features better automated detection of explosives and higher baggage throughput than older 2D X-ray imaging technology. Nonetheless, some countries and airports hesitate to implement 3D systems due to their lower image quality and the concern that screeners will need extensive and specific training before they can be allowed to work with 3D imaging. Method: Screeners working with 2D imaging (2D screeners) and screeners working with 3D imaging (3D screeners) conducted a simulated hold baggage screening task with both types of imaging. Differences in image quality of the imaging systems were assessed with the standard procedure for 2D imaging. Results: Despite lower image quality, screeners’ detection performance with 3D imaging was similar to that with 2D imaging. 3D screeners revealed higher detection performance with both types of imaging than 2D screeners. Conclusion: Features of 3D imaging systems (3D image rotation and slicing) seem to compensate for lower image quality. Visual inspection competency acquired with one type of imaging seems to transfer to visual inspection with the other type of imaging. Application: Replacing older 2D with newer 3D imaging systems can be recommended. 2D screeners do not need extensive and specific training to achieve comparable detection performance with 3D imaging. Current image quality standards for 2D imaging need revision before they can be applied to 3D imaging.

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32

Logadottir, A., S. Korreman, and P. M. Petersen. "COMPARISON OF PROSTATE LOCALIZATION WITH 2D-2D AND 3D IMAGES." Radiotherapy and Oncology 92 (August 2009): S179—S180. http://dx.doi.org/10.1016/s0167-8140(12)73061-x.

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33

Jankoska, Maja. "Application CAD methods in 3D clothing design." Tekstilna industrija 68, no. 4 (2020): 31–37. http://dx.doi.org/10.5937/tekstind2004031j.

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Modeling virtual garments is known as a very laborious process, which includes designing 2D patterns, positioning, and sewing them in 3D, performing a physically-based simulation, and then iteratively adjusting patterns and parameters, repeating the process until the expected effect is achieved. The aim of this paper is to make a 2D pattern and 3D simulation of a men's shirt. First, the computer construction of the men's shirt model was made on a sketch-based, i.e. a 2D pattern is developed. Secondly, 2D pattern is developed by flattening 3D surface patches, then a 3D fine garment is formed directly based on the information of sewing relations and correspondence between 3D surfaces and 2D patterns. The method is able to design 3D garments and 2D patterns efficiently and accurately.

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34

Visby, Lasse, Charlotte Burup Kristensen, Frederik Holm Grund Pedersen, Per Ejlstrup Sigvardsen, Klaus Fuglsang Kofoed, Christian Hassager, and Rasmus Møgelvang. "Assessment of left ventricular outflow tract and aortic root: comparison of 2D and 3D transthoracic echocardiography with multidetector computed tomography." European Heart Journal - Cardiovascular Imaging 20, no. 10 (March 16, 2019): 1156–63. http://dx.doi.org/10.1093/ehjci/jez045.

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Abstract Aims Accurate echocardiographic assessment of left ventricular outflow tract (LVOT) and the aortic root is necessary for risk stratification and choice of appropriate treatment in patients with pathologies of the aortic valve and aortic root. Conventional 2D transthoracic echocardiographic (TTE) assessment is based on the assumption of a circular shaped LVOT and aortic root, although previous studies have indicated a more ellipsoid shape. 3D TTE and multidetector computed tomography (MDCT) applies planimetry and are not dependent on geometrical assumptions. The aim was to test accuracy, feasibility, and reproducibility of 3D TTE compared to 2D TTE assessment of LVOT and aortic root areas, with MDCT as reference. Methods and results We examined 51 patients with 2D/3D TTE and MDCT at the same day. All patients were re-examined with 2D/3D TTE on a different day to evaluate 2D and 3D re-test variability. Areas of LVOT, aortic annulus, and sinus were assessed using 2D, 3D TTE, and MDCT. Both 2D/3D TTE underestimated the areas compared to MDCT; however, 3D TTE areas were significantly closer to MDCT-areas. 2D vs. 3D mean MDCT-differences: LVOT 1.61 vs. 1.15 cm2, P = 0.019; aortic annulus 1.96 vs. 1.06 cm2, P < 0.001; aortic sinus 1.66 vs. 1.08 cm2, P = 0.015. Feasibility was 3D 76–79% and 2D 88–90%. LVOT and aortic annulus areas by 3D TTE had lowest variabilities; intraobserver coefficient of variation (CV) 9%, re-test variation CV 18–20%. Conclusion Estimation of LVOT and aortic root areas using 3D TTE is feasible, more precise and more accurate than 2D TTE.

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Yang, Guangjie, Aidi Gong, Pei Nie, Lei Yan, Wenjie Miao, Yujun Zhao, Jie Wu, Jingjing Cui, Yan Jia, and Zhenguang Wang. "Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma." Molecular Imaging 18 (January 1, 2019): 153601211988316. http://dx.doi.org/10.1177/1536012119883161.

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Objective: To evaluate the value of 2-dimensional (2D) and 3-dimensional (3D) computed tomography texture analysis (CTTA) models in distinguishing fat-poor angiomyolipoma (fpAML) from chromophobe renal cell carcinoma (chRCC). Methods: We retrospectively enrolled 32 fpAMLs and 24 chRCCs. Texture features were extracted from 2D and 3D regions of interest in triphasic CT images. The 2D and 3D CTTA models were constructed with the least absolute shrinkage and selection operator algorithm and texture scores were calculated. The diagnostic performance of the 2D and 3D CTTA models was evaluated with respect to calibration, discrimination, and clinical usefulness. Results: Of the 177 and 183 texture features extracted from 2D and 3D regions of interest, respectively, 5 2D features and 8 3D features were selected to build 2D and 3D CTTA models. The 2D CTTA model (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.695-0.927) and the 3D CTTA model (AUC, 0.915; 95% CI, 0.838-0.993) showed good discrimination and calibration ( P > .05). There was no significant difference in AUC between the 2 models ( P = .093). Decision curve analysis showed the 3D model outperformed the 2D model in terms of clinical usefulness. Conclusions: The CTTA models based on contrast-enhanced CT images had a high value in differentiating fpAML from chRCC.

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36

Bahsan, Erly, and Rifani Fakhriyyanti. "Comparison of 2D and 3D Stability Analyses for Natural Slope." International Journal of Engineering & Technology 7, no. 4.35 (November 30, 2018): 662. http://dx.doi.org/10.14419/ijet.v7i4.35.23085.

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Slope stability analyses are performed mostly as a two-dimensional (2D) section under the assumption of plane strain conditions, without much consideration to the impact of three-dimensional (3D) shapes. For natural slopes that have the complexities of slope surfaces, 3D modeling may also be considered since it can represent the more realistic geometry of the slope. However, previous studies show that the factor of safety (FS) as a result of 3D analyses mostly overestimated the FS from 2D analyses. This may lead to a long discussion on whether the 3D analysis is still applicable for the natural slopes, and could it represent the same results as the 2D analysis. This study was conducted using the finite element method for calculating the 2D and 3D FS of Pasir Muncang natural slope in order to observe differences of FS resulted from both analyses. A comparison of the FS from the 2D and 3D analyses, and also verification of sensitivity on several factors that impact the 2D and 3D models have been performed. The results of this study has indicated that some factors such as soil parameters, contour interval, and mesh coarseness greatly affect the results of the 2D and 3D calculations. Having carefully selected the aforementioned factors as the inputs for calculations, the difference between the FS values of 3D and 2D analyses becomes smaller. The final result of FS for this case study from the 3D analysis was still higher than the one from the 2D analysis, with the ratio of FS from 3D to FS from 2D was 1.44. It can be inferred that the use of 3D analyses needs more accurate data selections compared to the 2D analyses.

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Choi, Chang-Hyuk, Hee-Chan Kim, Daewon Kang, and Jun-Young Kim. "Comparative study of glenoid version and inclination using two-dimensional images from computed tomography and three-dimensional reconstructed bone models." Clinics in Shoulder and Elbow 23, no. 3 (September 1, 2020): 119–24. http://dx.doi.org/10.5397/cise.2020.00220.

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Background: This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models.Methods: Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise).Results: Mean glenoid version and inclination in 2D measurements were –1.705º and 9.08º, respectively, while those in 3D measurements were 2.635º and 7.23º. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while those in 3D measurements was 0.853 and 0.845.Conclusions: The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.

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38

Sawada, Tadamasa. "Influence of 3D Centro-Symmetry on a 2D Retinal Image." Symmetry 12, no. 11 (November 12, 2020): 1863. http://dx.doi.org/10.3390/sym12111863.

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An object is 3D centro-symmetrical if the object can be segmented into two halves and the relationship between them can be represented by a combination of reflection about a plane and a rotation through 180° about an axis that is normal to the plane. A 2D orthographic image of the 3D centro-symmetrical object is always 2D rotation-symmetrical. Note that the human visual system is known to be sensitive to 2D rotational symmetry. This human sensitivity to 2D rotational symmetry might also be used to detect 3D centro-symmetry. If it is, can this detection of 3D centro-symmetry be helpful for the perception of 3D? In this study, the geometrical properties of 3D centro-symmetry and its 2D orthographic and perspective projections were examined to find out whether 3D centro-symmetry plays any role in the perception of 3D. I found that, from a theoretical point-of-view, it is unlikely that 3D centro-symmetry can be used by the human visual system to organize a 2D image of an object in a way that makes it possible to recover the 3D shape of an object from its 2D image.

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Poulsen, Henning Friis, and Dorte Juul Jensen. "From 2D to 3D Microtexture Investigations." Materials Science Forum 408-412 (August 2002): 49–66. http://dx.doi.org/10.4028/www.scientific.net/msf.408-412.49.

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Bollen, Anne-Marie. "Cephalometry in orthodontics: 2D and 3D." American Journal of Orthodontics and Dentofacial Orthopedics 156, no. 1 (July 2019): 161. http://dx.doi.org/10.1016/j.ajodo.2019.04.021.

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41

Le Guern, C. "Urban Geochemistry: from 2D to 3D." Procedia Engineering 209 (2017): 26–33. http://dx.doi.org/10.1016/j.proeng.2017.11.126.

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42

Couprie, Michel, Gilles Bertrand, and Yukiko Kenmochi. "Discretization in 2D and 3D orders." Graphical Models 65, no. 1-3 (May 2003): 77–91. http://dx.doi.org/10.1016/s1524-0703(03)00003-1.

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43

Benoit, B., and P. Bach-Segura. "Pathologie rachidienne : 2D, 3D, IRM, scanner." Journal de Radiologie 88, no. 10 (October 2007): 1335. http://dx.doi.org/10.1016/s0221-0363(07)80914-0.

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Lazarian, A., G. Kowal, E. Vishniac, K. Kulpa-Dubel, and K. Otmianowska-Mazur. "2D and 3D turbulent magnetic reconnection." Proceedings of the International Astronomical Union 5, H15 (November 2009): 434–35. http://dx.doi.org/10.1017/s174392131001015x.

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AbstractA magnetic field embedded in a perfectly conducting fluid preserves its topology for all times. Although ionized astrophysical objects, like stars and galactic disks, are almost perfectly conducting, they show indications of changes in topology, magnetic reconnection, on dynamical time scales. Reconnection can be observed directly in the solar corona, but can also be inferred from the existence of large scale dynamo activity inside stellar interiors. Solar flares and gamma ray busts are usually associated with magnetic reconnection. Previous work has concentrated on showing how reconnection can be rapid in plasmas with very small collision rates. Here we present numerical evidence, based on three dimensional simulations, that reconnection in a turbulent fluid occurs at a speed comparable to the rms velocity of the turbulence, regardless of the value of the resistivity. In particular, this is true for turbulent pressures much weaker than the magnetic field pressure so that the magnetic field lines are only slightly bent by the turbulence. These results are consistent with the proposal by Lazarian & Vishniac (1999) that reconnection is controlled by the stochastic diffusion of magnetic field lines, which produces a broad outflow of plasma from the reconnection zone. This work implies that reconnection in a turbulent fluid typically takes place in approximately a single eddy turnover time, with broad implications for dynamo activity and particle acceleration throughout the universe. In contrast, the reconnection in 2D configurations in the presence of turbulence depends on resistivity, i.e. is slow.

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Kunikowski, Bartłomiej. "KONWERSJA OBRAZÓW 2D DO MODELU 3D." ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA 1, no. 8 (August 27, 2019): 7–10. http://dx.doi.org/10.15199/13.2019.8.1.

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Weiger, M. "2D SENSE for faster 3D MRI." Magnetic Resonance Materials in Biology, Physics, and Medicine 14, no. 1 (March 1, 2002): 10–19. http://dx.doi.org/10.1016/s1352-8661(01)00152-1.

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La-Placa, Maria-Grazia, Lidón Gil-Escrig, Dengyang Guo, Francisco Palazon, Tom J. Savenije, Michele Sessolo, and Henk J. Bolink. "Vacuum-Deposited 2D/3D Perovskite Heterojunctions." ACS Energy Letters 4, no. 12 (November 5, 2019): 2893–901. http://dx.doi.org/10.1021/acsenergylett.9b02224.

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Twarog, N. R., E. H. Adelson, and M. F. Tappen. "Segmenting 2D Shapes using 3D Inflation." Journal of Vision 11, no. 11 (September 23, 2011): 851. http://dx.doi.org/10.1167/11.11.851.

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Huang, Weicheng, Xun Cao, Ke Lu, Qionghai Dai, and Alan Conrad Bovik. "Toward Naturalistic 2D-to-3D Conversion." IEEE Transactions on Image Processing 24, no. 2 (February 2015): 724–33. http://dx.doi.org/10.1109/tip.2014.2385474.

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De Floriani, Leila. "Using 2D Maps for 3D Localization." Computer 49, no. 3 (March 2016): 5. http://dx.doi.org/10.1109/mc.2016.87.

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