Literatura académica sobre el tema "2D Images - 3D Models"
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Artículos de revistas sobre el tema "2D Images - 3D Models"
Yang, Guangjie, Aidi Gong, Pei Nie, Lei Yan, Wenjie Miao, Yujun Zhao, Jie Wu, Jingjing Cui, Yan Jia y Zhenguang Wang. "Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma". Molecular Imaging 18 (1 de enero de 2019): 153601211988316. http://dx.doi.org/10.1177/1536012119883161.
Texto completoIyoho, Anthony E., Jonathan M. Young, Vladislav Volman, David A. Shelley, Laurel J. Ng y Henry Wang. "3D Tibia Reconstruction Using 2D Computed Tomography Images". Military Medicine 184, Supplement_1 (1 de marzo de 2019): 621–26. http://dx.doi.org/10.1093/milmed/usy379.
Texto completoOsadchy, Margarita, David Jacobs, Ravi Ramamoorthi y David Tucker. "Using specularities in comparing 3D models and 2D images". Computer Vision and Image Understanding 111, n.º 3 (septiembre de 2008): 275–94. http://dx.doi.org/10.1016/j.cviu.2007.12.004.
Texto completoAvesta, Arman, Sajid Hossain, MingDe Lin, Mariam Aboian, Harlan M. Krumholz y Sanjay Aneja. "Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation". Bioengineering 10, n.º 2 (1 de febrero de 2023): 181. http://dx.doi.org/10.3390/bioengineering10020181.
Texto completoPetre, Raluca-Diana y Titus Zaharia. "3D Model-Based Semantic Categorization of Still Image 2D Objects". International Journal of Multimedia Data Engineering and Management 2, n.º 4 (octubre de 2011): 19–37. http://dx.doi.org/10.4018/jmdem.2011100102.
Texto completoLi, Yu, Shaohua Li y Bo Zhang. "Constructing of 3D Fluvial Reservoir Model Based on 2D Training Images". Applied Sciences 13, n.º 13 (25 de junio de 2023): 7497. http://dx.doi.org/10.3390/app13137497.
Texto completoZhong, Chunyan, Yanli Guo, Haiyun Huang, Liwen Tan, Yi Wu y Wenting Wang. "Three-Dimensional Reconstruction of Coronary Arteries and Its Application in Localization of Coronary Artery Segments Corresponding to Myocardial Segments Identified by Transthoracic Echocardiography". Computational and Mathematical Methods in Medicine 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/783939.
Texto completoChoi, Chang-Hyuk, Hee-Chan Kim, Daewon Kang y 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, n.º 3 (1 de septiembre de 2020): 119–24. http://dx.doi.org/10.5397/cise.2020.00220.
Texto completoFalah .K, Rasha y Rafeef Mohammed .H. "Convert 2D shapes in to 3D images". Journal of Al-Qadisiyah for computer science and mathematics 9, n.º 2 (20 de agosto de 2017): 19–23. http://dx.doi.org/10.29304/jqcm.2017.9.2.146.
Texto completoSezer, Sümeyye, Vitoria Piai, Roy P. C. Kessels y Mark ter Laan. "Information Recall in Pre-Operative Consultation for Glioma Surgery Using Actual Size Three-Dimensional Models". Journal of Clinical Medicine 9, n.º 11 (13 de noviembre de 2020): 3660. http://dx.doi.org/10.3390/jcm9113660.
Texto completoTesis sobre el tema "2D Images - 3D Models"
Zhang, Yan. "Feature-based automatic registration of images with 2D and 3D models". Thesis, University of Central Lancashire, 2006. http://clok.uclan.ac.uk/21603/.
Texto completoStebbing, Richard. "Model-based segmentation methods for analysis of 2D and 3D ultrasound images and sequences". Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bf.
Texto completoLópez, Picazo Mirella. "3D subject-specific shape and density modeling of the lumbar spine from 2D DXA images for osteoporosis assessment". Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/666513.
Texto completoLa osteoporosis es la enfermedad ósea más común, con una morbilidad y mortalidad significativas causadas por el aumento de la fragilidad ósea y la susceptibilidad a las fracturas. La absorciometría de rayos X de energía dual (DXA, por sus siglas en inglés) es la técnica de referencia para la evaluación de la osteoporosis y del riesgo de fracturas en la columna vertebral. Sin embargo, el análisis estándar de las imágenes DXA solo proporciona mediciones 2D y no diferencia entre los compartimentos óseos; tampoco evalúa la densidad ósea en el cuerpo vertebral, que es donde se producen la mayoría de las fracturas osteoporóticas. La tomografía computarizada cuantitativa (QCT, por sus siglas en inglés) es una técnica alternativa que supera las limitaciones del diagnóstico basado en DXA. Sin embargo, debido al alto costo y la dosis de radiación, la QCT no se usa para el diagnóstico de la osteoporosis. En esta tesis, se propone un método que proporciona una estimación personalizada de la forma 3D y la densidad de la columna vertebral en la zona lumbar a partir de una única imagen DXA anteroposterior. El método se basa en un modelo estadístico 3D de forma y densidad creado a partir de un conjunto de entrenamiento de exploraciones QCT. La estimación 3D personalizada de forma y densidad se obtiene al registrar y ajustar el modelo estadístico con la imagen DXA. Se segmentan los compartimentos óseos corticales y trabeculares utilizando un algoritmo basado en modelos. Se realizan mediciones 3D en diferentes regiones vertebrales y compartimentos óseos. La precisión de los métodos propuestos se evalúa comparando las mediciones 3D derivadas de DXA con las derivadas de QCT. También se realizan dos estudios de casos y controles: un estudio retrospectivo que evalúa la capacidad de las mediciones 3D derivadas de DXA en la columna lumbar para discriminar entre sujetos con fracturas vertebrales relacionadas con la osteoporosis y sujetos control; y un estudio que evalúa la asociación entre las mediciones 3D derivadas de DXA en la columna lumbar y las fracturas de cadera relacionadas con la osteoporosis. En ambos estudios, se encuentran asociaciones más fuertes entre las fracturas relacionadas con la osteoporosis y las mediciones 3D derivadas de DXA en comparación con las mediciones estándar 2D. La tecnología desarrollada dentro de esta tesis ofrece un análisis en 3D de la columna lumbar, que podría mejorar la evaluación de la osteoporosis y el riesgo de fractura en pacientes que se sometieron a una exploración DXA estándar de la columna lumbar sin ningún examen adicional.
Wasswa, William. "3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting". Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/23777.
Texto completoKarlsson, Edlund Patrick. "Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells". Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9201.
Texto completoHua, Xiaoben y Yuxia Yang. "A Fusion Model For Enhancement of Range Images". Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2203.
Texto completoRoom 401, No.56, Lane 21, Yin Gao Road, Shanghai, China
Ben, Abdallah Hamdi. "Inspection d'assemblages aéronautiques par vision 2D/3D en exploitant la maquette numérique et la pose estimée en temps réel Three-dimensional point cloud analysis for automatic inspection of complex aeronautical mechanical assemblies Automatic inspection of aeronautical mechanical assemblies by matching the 3D CAD model and real 2D images". Thesis, Ecole nationale des Mines d'Albi-Carmaux, 2020. http://www.theses.fr/2020EMAC0001.
Texto completoThis thesis makes part of a research aimed towards innovative digital tools for the service of what is commonly referred to as Factory of the Future. Our work was conducted in the scope of the joint research laboratory "Inspection 4.0" founded by IMT Mines Albi/ICA and the company DIOTA specialized in the development of numerical tools for Industry 4.0. In the thesis, we were interested in the development of systems exploiting 2D images or (and) 3D point clouds for the automatic inspection of complex aeronautical mechanical assemblies (typically an aircraft engine). The CAD (Computer Aided Design) model of the assembly is at our disposal and our task is to verify that the assembly has been correctly assembled, i.e. that all the elements constituting the assembly are present in the right position and at the right place. The CAD model serves as a reference. We have developed two inspection scenarios that exploit the inspection systems designed and implemented by DIOTA: (1) a scenario based on a tablet equipped with a camera, carried by a human operator for real-time interactive control, (2) a scenario based on a robot equipped with sensors (two cameras and a 3D scanner) for fully automatic control. In both scenarios, a so-called localisation camera provides in real-time the pose between the CAD model and the sensors (which allows to directly link the 3D digital model with the 2D images or the 3D point clouds analysed). We first developed 2D inspection methods, based solely on the analysis of 2D images. Then, for certain types of inspection that could not be performed by using 2D images only (typically requiring the measurement of 3D distances), we developed 3D inspection methods based on the analysis of 3D point clouds. For the 3D inspection of electrical cables, we proposed an original method for segmenting a cable within a point cloud. We have also tackled the problem of automatic selection of best view point, which allows the inspection sensor to be placed in an optimal observation position. The developed methods have been validated on many industrial cases. Some of the inspection algorithms developed during this thesis have been integrated into the DIOTA Inspect© software and are used daily by DIOTA's customers to perform inspections on industrial sites
Truong, Michael Vi Nguyen. "2D-3D registration of cardiac images". Thesis, King's College London (University of London), 2014. https://kclpure.kcl.ac.uk/portal/en/theses/2d3d-registration-of-cardiac-images(afef93e6-228c-4bc7-aab0-94f1e1ecf006).html.
Texto completoJones, Jonathan-Lee. "2D and 3D segmentation of medical images". Thesis, Swansea University, 2015. https://cronfa.swan.ac.uk/Record/cronfa42504.
Texto completoLiu, Jianxin. "A porosity-based model for coupled thermal-hydraulic-mechanical processes". University of Western Australia. Centre for Petroleum, Fuels and Energy, 2010. http://theses.library.uwa.edu.au/adt-WU2010.0113.
Texto completoLibros sobre el tema "2D Images - 3D Models"
Jones, Alun Gwyn. Recovering 3D shape from 2D images. Manchester: University of Manchester, 1995.
Buscar texto completoBairstow, John E. N. Design modelling: Visualising ideas in 2D and 3D. London: Hodder & Stoughton, 1999.
Buscar texto completoWiedemann, Julius. Digital beauties: 2D & 3D computer generated digital models, virtual idols and characters. Köln: Taschen, 2002.
Buscar texto completoSüveg, Ildikó. Reconstruction of 3D building models from aerial images and maps. Delft: Netherlands Geodetic Commission, 2003.
Buscar texto completoEdexcel, ed. Art and Design.GNVQ Intermediate.Unit 1:2D and 3D Visual Language.Student Preparatory Work (Pre-seen Images). January 2003. London: Edexcel, 2001.
Buscar texto completoSong, Weidong. Yao gan ying xiang ji he jiu zheng yu san wei chong jian =: Geometric correction and 3D reconstruction for remote sensing images. 8a ed. Beijing Shi: Ce hui chu ban she, 2011.
Buscar texto completoCappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2013 Florence. Florence: Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-372-4.
Texto completoCappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2015 Florence. Florence: Firenze University Press, 2015. http://dx.doi.org/10.36253/978-88-6655-759-3.
Texto completoCappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2014 Florence. Florence: Firenze University Press, 2014. http://dx.doi.org/10.36253/978-88-6655-573-5.
Texto completoNechaev, Vladimir, Andrey Shuba, Stanislav Gridnev y Vitaliy Topolov. Dimensional effects in phase transitions and physical properties of ferroics. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1898400.
Texto completoCapítulos de libros sobre el tema "2D Images - 3D Models"
Sándor, Viktória, Mathias Bank, Kristina Schinegger y Stefan Rutzinger. "Collapsing Complexities: Encoding Multidimensional Architecture Models into Images". En Computational Design and Robotic Fabrication, 371–81. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8637-6_32.
Texto completoXie, Xianghua, Si Yong Yeo, Majid Mirmehdi, Igor Sazonov y Perumal Nithiarasu. "Image Gradient Based Level Set Methods in 2D and 3D". En Deformation Models, 101–20. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5446-1_4.
Texto completoOhkubo, Ryo, Ryo Kurazume y Katsushi Ikeuchi. "Simultaneous Registration of 2D Images onto 3D Models for Texture Mapping". En Digitally Archiving Cultural Objects, 237–78. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_13.
Texto completoZhang, Hang y Ye Huang. "Machine Learning Aided 2D-3D Architectural Form Finding at High Resolution". En Proceedings of the 2020 DigitalFUTURES, 159–68. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_15.
Texto completoBrumana, R. "How to Measure Quality Models? Digitization into Informative Models Re-use". En 3D Research Challenges in Cultural Heritage III, 77–102. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35593-6_5.
Texto completoXu, Chenfeng, Shijia Yang, Tomer Galanti, Bichen Wu, Xiangyu Yue, Bohan Zhai, Wei Zhan, Peter Vajda, Kurt Keutzer y Masayoshi Tomizuka. "Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models". En Lecture Notes in Computer Science, 638–56. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19836-6_36.
Texto completoTilborghs, Sofie, Tom Dresselears, Piet Claus, Jan Bogaert y Frederik Maes. "3D Left Ventricular Segmentation from 2D Cardiac MR Images Using Spatial Context". En Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 90–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39074-7_10.
Texto completoVotsis, George, Nicolas Tsapatsoulis, Kostas Karpouzis y Stefanos Kollias. "A Simplified Representation of 3D Human Faces adapted from 2D Images". En Noblesse Workshop on Non-Linear Model Based Image Analysis, 39–45. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1597-7_7.
Texto completoVani, K. S., Rupesh Sapkota, Sparsh Shrestha y Srujan B. "Creating a 3D Model from 2D Images Using Convolution Neural Network". En Advances in Intelligent Systems and Computing, 661–67. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8443-5_56.
Texto completoMing, Geng, Bo Zhou, Xiaohua Luo, Ren Ling y Mingxiang Zhou. "Rail Surface Defect Detection Method Based on Deep Learning Method with 3D Range Image". En Advances in Frontier Research on Engineering Structures, 45–59. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8657-4_5.
Texto completoActas de conferencias sobre el tema "2D Images - 3D Models"
Li, Liang, Hanzi Wang, Tat-Jun Chin, David Suter y Shusheng Zhang. "Retrieving 3D CAD models using 2D images with optimized weights". En 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5646952.
Texto completoAbreu de Souza, Mauren, Andriy Guilherme Krefer, Gustavo Benvenutti Borba, Tania Mezzadri Centeno y Humberto Remigio Gamba. "Combining 3D models with 2D infrared images for medical applications". En 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7318876.
Texto completoUmarani, S. M. y P. Archana. "Computational Analysis of Respiratory Tract with 2D and 3D Models". En 2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII). IEEE, 2018. http://dx.doi.org/10.1109/icbsii.2018.8524688.
Texto completoYueh-Ling Lin y Mao-Jiun J. Wang. "Constructing 3D human model from 2D images". En EM2010). IEEE, 2010. http://dx.doi.org/10.1109/icieem.2010.5645897.
Texto completoZhang, Dingwen, Junwei Han, Yang Yang y Dong Huang. "Learning Category-Specific 3D Shape Models from Weakly Labeled 2D Images". En 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2017. http://dx.doi.org/10.1109/cvpr.2017.382.
Texto completoHodge, Adam C. y Hanif M. Ladak. "3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models". En Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260668.
Texto completoHodge, Adam C. y Hanif M. Ladak. "3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models". En Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4397911.
Texto completoTutar, Ismail B., Sayan D. Pathak y Yongmin Kim. "3D prostate shape modeling from sparsely acquired 2D images using deformable models". En Medical Imaging 2004, editado por Robert L. Galloway, Jr. SPIE, 2004. http://dx.doi.org/10.1117/12.536809.
Texto completoRoy, Anirban, Sujeong Kim, Min Yin, Eric Yeh, Takuma Nakabayashi, Matt Campbell, Ian Keough y Yoshito Tsuji. "A learning-based framework for generating 3D building models from 2D images". En 2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION). IEEE, 2022. http://dx.doi.org/10.1109/destion56136.2022.00014.
Texto completoAlbus, John E. "Applications of an efficient algorithm for locating 3D models in 2D images". En Aerospace/Defense Sensing and Controls, editado por Firooz A. Sadjadi. SPIE, 1998. http://dx.doi.org/10.1117/12.323859.
Texto completoInformes sobre el tema "2D Images - 3D Models"
Basri, Ronen y Daphna Weinshall. Distance Metric between 3D Models and 2D Images for Recognition and Classification. Fort Belvoir, VA: Defense Technical Information Center, julio de 1992. http://dx.doi.org/10.21236/ada260069.
Texto completoArroyo, Marcos, Riccardo Rorato, Marco Previtali y Matteo Ciantia. 2D Image-based calibration of rolling resistance in 3D discrete element models of sand. University of Dundee, diciembre de 2021. http://dx.doi.org/10.20933/100001229.
Texto completoHabib, Ayman, Darcy M. Bullock, Yi-Chun Lin y Raja Manish. Road Ditch Line Mapping with Mobile LiDAR. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317354.
Texto completoDE CUBBER, Ine y Jos VAN ORSHOVEN. Unstandardized terminology complicates the communication about 2D and 3D spatial data models. Cogeo@oeaw-giscience, septiembre de 2011. http://dx.doi.org/10.5242/iamg.2011.0273.
Texto completoToutin, Th, R. Chénier y Y. Carbonneau. 3D Models for High Resolution Images: Examples with Quickbird, IKONOS, and EROS. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2002. http://dx.doi.org/10.4095/219879.
Texto completoBlundell, S. y Philip Devine. Creation, transformation, and orientation adjustment of a building façade model for feature segmentation : transforming 3D building point cloud models into 2D georeferenced feature overlays. Engineer Research and Development Center (U.S.), enero de 2020. http://dx.doi.org/10.21079/11681/35115.
Texto completoPaul, D., E. A. de Kemp y M. R. St-Onge. Canada in 3D (C3D) the next generation view of the geology of Canada. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331348.
Texto completoWitzig, Andreas, Camilo Tello, Franziska Schranz, Johannes Bruderer y Matthias Haase. Quantifying energy-saving measures in office buildings by simulation in 2D cross sections. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541623658.
Texto completoMidak, Liliia Ya, Ivan V. Kravets, Olga V. Kuzyshyn, Khrystyna V. Berladyniuk, Khrystyna V. Buzhdyhan, Liliia V. Baziuk y Aleksandr D. Uchitel. Augmented reality in process of studying astronomic concepts in primary school. [б. в.], noviembre de 2020. http://dx.doi.org/10.31812/123456789/4411.
Texto completoMojidra, Rushil y Keri Ryan. Influence of Vertical Ground Motion on Bridges Isolated with Spherical Sliding Bearings. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, diciembre de 2019. http://dx.doi.org/10.55461/rynq3624.
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