Academic literature on the topic '3D visualisation and segmentation'
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Journal articles on the topic "3D visualisation and segmentation":
Gaifas, Lorenzo, Moritz A. Kirchner, Joanna Timmins, and Irina Gutsche. "Blik is an extensible 3D visualisation tool for the annotation and analysis of cryo-electron tomography data." PLOS Biology 22, no. 4 (April 30, 2024): e3002447. http://dx.doi.org/10.1371/journal.pbio.3002447.
Jung, Y., H. Kim, B. Park, H. Lee, B. Kim, M. Bang, J. Lee, M. Oh, and G. Cho. "EP02.14: The new 3D‐based fetal segmentation and visualisation method." Ultrasound in Obstetrics & Gynecology 62, S1 (October 2023): 107. http://dx.doi.org/10.1002/uog.26634.
Kang, Hanwen, and Chao Chen. "Fruit detection, segmentation and 3D visualisation of environments in apple orchards." Computers and Electronics in Agriculture 171 (April 2020): 105302. http://dx.doi.org/10.1016/j.compag.2020.105302.
Colombo, E., T. Fick, G. Esposito, M. Germans, L. Regli, and T. van Doormaal. "Segmentation techniques of cerebral arteriovenous malformations for 3D visualisation: a systematic review." Brain and Spine 2 (2022): 101415. http://dx.doi.org/10.1016/j.bas.2022.101415.
Dury, Richard, Rob Dineen, Anbarasu Lourdusamy, and Richard Grundy. "Semi-automated medulloblastoma segmentation and influence of molecular subgroup on segmentation quality." Neuro-Oncology 21, Supplement_4 (October 2019): iv14. http://dx.doi.org/10.1093/neuonc/noz167.060.
Patekar, Rahul, Prashant Shukla Kumar, Hong-Seng Gan, and Muhammad Hanif Ramlee. "Automated Knee Bone Segmentation and Visualisation Using Mask RCNN and Marching Cube: Data From The Osteoarthritis Initiative." ASM Science Journal 17 (April 13, 2022): 1–7. http://dx.doi.org/10.32802/asmscj.2022.968.
Luo, Tess X. H., Wallace W. L. Lai, and Zhanzhan Lei. "Intensity Normalisation of GPR C-Scans." Remote Sensing 15, no. 5 (February 27, 2023): 1309. http://dx.doi.org/10.3390/rs15051309.
Medved, M. S., S. D. Rud, G. E. Trufanov, and D. S. Lebedev. "The intraoperative visualisation technique during lead implantation into the cardiac conductive system: aspects of computed tomography: prospective study." Diagnostic radiology and radiotherapy 14, no. 3 (October 5, 2023): 46–52. http://dx.doi.org/10.22328/2079-5343-2023-14-3-46-52.
Forte, Mari Nieves Velasco, Tarique Hussain, Arno Roest, Gorka Gomez, Monique Jongbloed, John Simpson, Kuberan Pushparajah, Nick Byrne, and Israel Valverde. "Living the heart in three dimensions: applications of 3D printing in CHD." Cardiology in the Young 29, no. 06 (June 2019): 733–43. http://dx.doi.org/10.1017/s1047951119000398.
Gende, Mateo, Joaquim De Moura, Jorge Novo, Pablo Charlon, and Marcos Ortega. "Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches." IEEE Access 9 (2021): 75993–6004. http://dx.doi.org/10.1109/access.2021.3082638.
Dissertations / Theses on the topic "3D visualisation and segmentation":
Mao, Bo. "Visualisation and Generalisation of 3D City Models." Doctoral thesis, KTH, Geoinformatik och Geodesi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-48174.
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Dufour, Alexandre. "Segmentation, suivi et visualisation d'objets biologiques en microscopie 3D par fluorescence : Approches par modèles déformables." Phd thesis, Université René Descartes - Paris V, 2007. http://tel.archives-ouvertes.fr/tel-00271191.
Les modèles déformables, également connus sous le nom de contours actifs, font actuellement partie des méthodes de pointe en analyse d'images pour la segmentation et le suivi d'objets grâce à leur robustesse, leur flexibilité et leur représentation à haut niveau sémantique des entités recherchées. Afin de les adapter à notre problématique, nous devons faire face à diverses difficultés. Tout d'abord, les méthodes existantes se réfèrent souvent aux variations locales d'intensité (ou gradients) de l'image pour détecter le contour des objets recherchés. Cette approche est inefficace en microscopie tridimensionnelle par fluorescence, où les gradients sont très peu prononcés selon l'axe de profondeur de l'image. Ensuite, nous devons gérer le suivi d'objets multiples susceptibles d'entrer en contact en évitant leur confusion. Enfin, nous devons mettre en place un système permettant de visualiser efficacement les contours durant leur déformation sans altérer les temps de calcul.
Dans la première partie de ce travail, nous pallions à ces problèmes en proposant un modèle de segmentation et de suivi multi-objets basé sur le formalisme des lignes de niveaux (ou level sets) et exploitant la fonctionnelle de Mumford et Shah. La méthode obtenue donne des résultats quantitatifs satisfaisants, mais ne se prête pas efficacement au rendu 3D de la scène, pour lequel nous sommes tributaires d'algorithmes dédiés à la reconstruction 3D (e.g. la méthode des "Marching Cubes"), souvent coûteux en mémoire et en temps de calcul. De plus, ces algorithmes peuvent induire des erreurs d'approximation et ainsi entraîner une mauvaise interprétation des résultats.
Dans la seconde partie, nous proposons une variation de la méthode précédente en remplaçant le formalisme des lignes de niveaux par celui des maillages triangulaires, très populaire dans le domaine de la conception assistée par ordinateur (CAO) pour leur rendu 3D rapide et précis. Cette nouvelle approche produit des résultats quantitatifs équivalents, en revanche le formalisme des maillages permet d'une part de réduire considérablement la complexité du problème et autorise d'autre part à effectuer un rendu 3D précis de la scène parallèlement au processus de segmentation, réduisant d'autant plus les temps de calculs.
Les performances des deux méthodes proposées sont d'abord évaluées puis comparées sur un jeu de données simulées reproduisant le mieux possible les caractéristiques des images réelles. Ensuite, nous nous intéressons plus particulièrement à l'évaluation de la méthode par maillages sur des données réelles, en évaluant la robustesse et la stabilité de quelques descripteurs de forme simples sur des expériences d'imagerie haut-débit. Enfin, nous présentons des applications concrètes de la méthode à des problématiques biologiques réelles, réalisées en collaboration avec d'autres équipes de l'Institut Pasteur de Corée.
Wang, Chen. "Large-scale 3D environmental modelling and visualisation for flood hazard warning." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/3350.
Bridge, Pete. "The development and evaluation of a novel 3D radiotherapy immersive outlining tool." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/123511/1/Peter%20Bridge%20Thesis.pdf.
Verdonck, Bert. "Segmentation, mesure et visualisation des vaisseaux sanguins à partir d'angiographies 3d par résonance magnétique et tomodensitométrie helicoidale." Paris, ENST, 1996. http://www.theses.fr/1996ENST0042.
Verdonck, Bert. "Segmentation, mesure et visualisation des vaisseaux sanguins à partir d'angiographies 3D par résonance magnétique et tomodensitométrie hélicoîdale /." Paris : École nationale supérieure des télécommunications, 1997. http://catalogue.bnf.fr/ark:/12148/cb36703841x.
Mention parallèle de titre ou de responsabilité : Blood vessel segmentation, quantification and visualization for 3D MR and spiral CT angiography. Textes en français ou en anglais. Bibliogr. p. 151-169. Résumé en français et en anglais.
Rekik, Wafa. "Fusion de données temporelles, ou 2D+t, et spatiales, ou 3D, pour la reconstruction de scènes 3D+t et traitement d'images sphériques : applications à la biologie cellulaire." Paris 6, 2007. http://www.theses.fr/2007PA066655.
Mercier, Corentin. "Geometrical modeling, simplification and visualization of brain white matter tractograms." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT048.
Tractography data (fibers) obtained from diffusion MRI present several challenges.In this thesis, we propose some useful methods and algorithms for simplification, visualization, and manipulation of these data.We introduce a new multi-resolution representation for tractograms, faster, and with higher geometric accuracy than existing simplification approaches.We also investigate various geometric representations and focus on moving least square (MLS) projection with algebraic point set surfaces (APSS), on which we reduce the complexity, allowing for the use of global kernels for analysis and modeling.A segmentation technique using the multi-resolution representation is presented, achieving better reproducibility than other approaches.Tractograms being massive, we also introduce a compression algorithm taking advantage of data obtention from diffusion MRI.The algorithm speed even allows for the direct use of compressed data for visualization, as it can be decompressed on-the-fly on the GPU.This research and the obtained results lie at the intersection between Computer Graphics and Medical Data Analysis, paving the way for numerous perspectives
Chassonnery, Pauline. "Modélisation mathématique en 3D de l'émergence de l'architecture des tissus conjonctifs." Electronic Thesis or Diss., Toulouse 3, 2023. http://www.theses.fr/2023TOU30354.
In this thesis, we investigate whether simple local mechanical interactions between a reduced set of components could govern the emergence of the 3D architecture of biological tissues. To explore this hypothesis, we develop two mathematical models. The first one, ECMmorpho-3D, aims at reproducing a non-specialised connective tissue and is reduced to the Extra-Cellular Matrix (ECM) component, that is a 3D dynamically connected fibre network. The second, ATmorpho-3D, is built by adding to this network spherical cells which spontaneously appear and grow in order to mimic the morphogenesis of Adipose Tissue (AT), a specialised connective tissue with major biomedical importance. We then construct a unified analysis framework to visualise, segment and quantitatively characterise the fibrous and cellular structures produced by our two models. It constitutes a generic tool for the 3D visualisation of systems composed of a mixture of spherical (cells) and rod-like (fibres) elements and for the automatic detection of in such systems of clusters of spherical objects separated by rod-like elements. This tool is also applicable to biological 3D microscopy images, enabling a comparison between in vivo and in silico structures. We study the structures produced by the model ECMmorpho-3D by performing numerical simula- tions. We show that this model is able to spontaneously generate different types of architectures, which we identify and characterise using our analysis framework. An in-depth parametric analysis lead us to identify an intermediate emerging variable, the number of crosslinks per fibre, which explains and partly predicts the fate of the modelled system. A temporal analysis reveals that the characteristic time-scale of the organisation process is a function of the network remodelling speed, and that all systems follow the same, unique evolutionary pathway. Finally, we use the model ATmorpho-3D to explore the influence of round cells over the organisation of a fibre network, taking as reference the model ECMmorpho-3D. We show that the number of cells can influence the local alignment of the fibres but not the global organisation of the network. On the other hand, the cells inside the network spontaneously organise into clusters with realistic morphological features very close to those of in vivo structures, surrounded by sheet-like fibre bundles. Moreover, the distribution of the different morphological types of clusters is similar in in silico and in vivo systems, suggesting that the model is able to produce realistic morphologies not only on the scale of one cluster but also on the scale of the whole system, reproducing the structural variability observed in biological samples. A parametric analysis reveals that the proportion in which each morphology is present in an in silico system is governed mainly by the remodelling characteristic of the fibres, pointing to the essential role of the ECM properties in AT architecture and function (in agreement with several biological results and previous 2D findings). The fact that these very simple mathematical models can produce realistic structures supports our hypothesis that biological tissues architecture could emerge spontaneously from local mechanical inter- actions between the tissue components, independently of the complex biological phenomena taking place around them. This opens many perspectives regarding our understanding of the fundamental principles governing how biological tissue architecture emerges during organogenesis, is maintained throughout life and can be affected by various pathological conditions. Potential applications range from tissue engineering to therapeutic treatment inducing regeneration in adult mammals
Robert, Bruno. "Echographie Tridimensionnelle." Phd thesis, Télécom ParisTech, 1999. http://tel.archives-ouvertes.fr/tel-00005697.
Books on the topic "3D visualisation and segmentation":
Shaughnessy, J. 3D visualisation. Manchester: University of Manchester, Department of ComputerScience, 1995.
Delengaigne, Anthony. Real-time 3D visualisation system. Oxford: Oxford Brookes University, 2004.
Hall, Tim. 3D visualisation of mobile robot sensr data. Manchester: University of Manchester, Department of Computer Science, 1997.
Ottoson, Patrik. Geographic indexing and data management for 3D-visualisation. Stockholm: Royal Institute of Technology, KTH, 2001.
Banik, Shantanu, Rangaraj M. Rangayyan, and Graham S. Boag. Landmarking and Segmentation of 3D CT Images. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-01635-6.
Jones, Michael. Automatic model acquisition for 3D object recognition and visualisation. Manchester: University of Manchester, 1995.
Buchroithner, Manfred. True-3D in Cartography: Autostereoscopic and Solid Visualisation of Geodata. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Wörz, Stefan. 3D parametric intensity models for the localization of 3D anatomical point landmarks and 3D segmentation of human vessels. Berlin: Akademische Verlagsgesellschaft Aka, 2006.
Romano, Alex. I, inventor: 3D mind technology. 4th ed. [Place of publication not identified]: A.R.P. Pub. Co., 2008.
Adamson, Paul. The design of CAD and the birth of CAID ; and, 2 x 2D = 3D: Visualisation of virtual 3D forms from 2D profiles. don]: Middlesex University, 1992.
Book chapters on the topic "3D visualisation and segmentation":
Skalski, Andrzej, Mirosław Socha, Mariusz Duplaga, Krzysztof Duda, and Tomasz Zieliński. "3D Segmentation and Visualisation of Mediastinal Structures Adjacent to Tracheobronchial Tree from CT Data." In Advances in Intelligent and Soft Computing, 523–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13105-9_52.
Tschumperlé, David, Christophe Tilmant, and Vincent Barra. "3D Visualisation." In Digital Image Processing with C++, 227–42. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003323693-10.
Young, Peter, and Malcolm Munro. "3D Software Visualisation." In Visual Representations and Interpretations, 341–50. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0563-3_38.
Buchroithner, Manfred F., and Claudia Knust. "True-3D in Cartography—Current Hard- and Softcopy Developments." In Geospatial Visualisation, 41–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-12289-7_3.
Weninger, W. J., Lars-Peter Kamolz, and S. H. Geyer. "3D Visualisation of Skin Substitutes." In Dermal Replacements in General, Burn, and Plastic Surgery, 87–96. Vienna: Springer Vienna, 2013. http://dx.doi.org/10.1007/978-3-7091-1586-2_8.
O’Brien, Scarlett, and Nagy Darwish. "3D Visualisation of the Spine." In Advances in Experimental Medicine and Biology, 139–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26462-7_7.
Mansutti, Alessandro, Mario Covarrubias Rodriguez, Monica Bordegoni, and Umberto Cugini. "Augmented Reality Visualisation System." In Tactile Display for Virtual 3D Shape Rendering, 101–8. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48986-5_8.
Heinen, Torsten, Martin May, and Benno Schmidt. "3d Visualisation in Spatial Data Infrastructures." In Smart Graphics, 222–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11536482_20.
v. Pichler, C., K. Radermacher, W. Boeckmann, G. Jakse, and G. Rau. "3D-visualisation for image guided surgery." In Lecture Notes in Computer Science, 309–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0029250.
Yazdy, Farzad E., Jon Tyrrell, Mark Riley, and Norman Winterbottom. "CARVUPP: Computer Assisted Radiological Visualisation Using Parallel Processing." In 3D Imaging in Medicine, 363–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_23.
Conference papers on the topic "3D visualisation and segmentation":
Zhang, Xiangrong, Feng Dong, Gordon Clapworthy, Youbing Zhao, and Licheng Jiao. "Semi-supervised Tissue Segmentation of 3D Brain MR Images." In 2010 14th International Conference Information Visualisation (IV). IEEE, 2010. http://dx.doi.org/10.1109/iv.2010.90.
Kopacsi, Sandor. "Interactive visualisation in 3D." In 2012 IEEE 3rd International Conference on Cognitive Infocommunications (CogInfoCom). IEEE, 2012. http://dx.doi.org/10.1109/coginfocom.2012.6421930.
Kapelner, Adam, Peter P. Lee, and Susan Holmes. "An Interactive Statistical Image Segmentation and Visualization System." In International Conference on Medical Information Visualisation - BioMedical Visualisation (MediVis 2007). IEEE, 2007. http://dx.doi.org/10.1109/medivis.2007.5.
Zhang, Yan, Bogdan J. Matuszewski, and Lik-Kwan Shark. "A Novel Medical Image Segmentation Method using Dynamic Programming." In International Conference on Medical Information Visualisation - BioMedical Visualisation (MediVis 2007). IEEE, 2007. http://dx.doi.org/10.1109/medivis.2007.2.
Shepherd, Phil. "3D Visual Thinking." In Electronic Visualisation and the Arts. BCS Learning & Development, 2018. http://dx.doi.org/10.14236/ewic/eva2018.48.
Ellis, David. "3D Visualisation for Seismic Processing." In Abu Dhabi International Petroleum Exhibition and Conference. Society of Petroleum Engineers, 2002. http://dx.doi.org/10.2118/78509-ms.
Krsek, Premysl, Michal Spanel, Petr Krupa, Ivo Marek, and Pavlina Cernochov. "Teeth And Jaw 3D Reconstrucion In Stomatology." In International Conference on Medical Information Visualisation - BioMedical Visualisation (MediVis 2007). IEEE, 2007. http://dx.doi.org/10.1109/medivis.2007.20.
Duncan, Justin, and Frankie Inguanez. "Social Distancing Crowd Segmentation, Estimation and Visualisation." In 2021 IEEE 11th International Conference on Consumer Electronics (ICCE-Berlin). IEEE, 2021. http://dx.doi.org/10.1109/icce-berlin53567.2021.9720028.
McFarlane, N. J. B., G. J. Clapworthy, A. Agrawal, M. Viceconti, F. Taddei, E. Schileo, and F. Baruffaldi. "3D Multiscale Visualisation for Medical Datasets." In 2008 Fifth International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics (MEDIVIS). IEEE, 2008. http://dx.doi.org/10.1109/medivis.2008.14.
Drenikow, Brandon, David Arppe, Pejman Mirza-Babaei, and Andrew Hogue. "Interactive 3D visualisation of playtesting data." In 2014 IEEE Games, Media, Entertainment (GEM) Conference. IEEE, 2014. http://dx.doi.org/10.1109/gem.2014.7048116.
Reports on the topic "3D visualisation and segmentation":
Toutin, Th, A. Redmond, E. Hoeppner, D. Hoja, and C. King. RADARSAT and DEM Data Fusion for 3D Visualisation Over the Reunion Island for Geoscientific Applications. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1998. http://dx.doi.org/10.4095/219317.
Buck, Valentin. Digital Earth Viewer. GEOMAR, 2023. http://dx.doi.org/10.3289/sw_6_2023.
Wang, Song. Metallic Material Image Segmentation by using 3D Grain Structure Consistency and Intra/Inter-Grain Model Information. Fort Belvoir, VA: Defense Technical Information Center, January 2015. http://dx.doi.org/10.21236/ada617033.
Cheniour, Amani, Amir Ziabari, Elena Tajuelo Rodriguez, Mohammed Alnaggar, Yann Le Pape, and T. M. Rosseel. Reconstruction of 3D Concrete Microstructures Combining High-Resolution Characterization and Convolutional Neural Network for Image Segmentation. Office of Scientific and Technical Information (OSTI), February 2024. http://dx.doi.org/10.2172/2311320.
Huang, Haohang, Erol Tutumluer, Jiayi Luo, Kelin Ding, Issam Qamhia, and John Hart. 3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. Illinois Center for Transportation, September 2022. http://dx.doi.org/10.36501/0197-9191/22-017.
Huang, Haohang, Jiayi Luo, Kelin Ding, Erol Tutumluer, John Hart, and Issam Qamhia. I-RIPRAP 3D Image Analysis Software: User Manual. Illinois Center for Transportation, June 2023. http://dx.doi.org/10.36501/0197-9191/23-008.
Blundell, S., and 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.), January 2020. http://dx.doi.org/10.21079/11681/35115.
Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Cheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li, and Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Burks, Thomas F., Victor Alchanatis, and Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, October 2009. http://dx.doi.org/10.32747/2009.7591739.bard.