Academic literature on the topic 'Anatomical simulator'
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Journal articles on the topic "Anatomical simulator"
Corte, Giuliano M., Melanie Humpenöder, Marcel Pfützner, Roswitha Merle, Mechthild Wiegard, Katharina Hohlbaum, Ken Richardson, Christa Thöne-Reineke, and Johanna Plendl. "Anatomical Evaluation of Rat and Mouse Simulators for Laboratory Animal Science Courses." Animals 11, no. 12 (December 1, 2021): 3432. http://dx.doi.org/10.3390/ani11123432.
Full textCoelho, Giselle, Samuel Zymberg, Marcos Lyra, Nelci Zanon, and Benjamin Warf. "New anatomical simulator for pediatric neuroendoscopic practice." Child's Nervous System 31, no. 2 (September 3, 2014): 213–19. http://dx.doi.org/10.1007/s00381-014-2538-9.
Full textWhite, Eoin, Muireann McMahon, Michael Walsh, J. Calvin Coffey, and Leonard O’Sullivan. "Creating Biofidelic Phantom Anatomies of the Colorectal Region for Innovations in Colorectal Surgery." Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 3, no. 1 (June 2014): 277–82. http://dx.doi.org/10.1177/2327857914031045.
Full textVenne, Gabriel, Greg Esau, Ryan T. Bicknell, and J. Tim Bryant. "3D Printed Anatomy-Specific Fixture for Consistent Glenoid Cavity Position in Shoulder Simulator." Journal of Healthcare Engineering 2018 (October 9, 2018): 1–6. http://dx.doi.org/10.1155/2018/2572730.
Full textMakic, Mary Beth Flynn, Karen Lovett, and M. Fareedul Azam. "Placement of an Esophageal Temperature Probe by Nurses." AACN Advanced Critical Care 23, no. 1 (January 1, 2012): 24–31. http://dx.doi.org/10.4037/nci.0b013e31823324f3.
Full textTai, Bruce L., Deborah Rooney, Francesca Stephenson, Peng-Siang Liao, Oren Sagher, Albert J. Shih, and Luis E. Savastano. "Development of a 3D-printed external ventricular drain placement simulator: technical note." Journal of Neurosurgery 123, no. 4 (October 2015): 1070–76. http://dx.doi.org/10.3171/2014.12.jns141867.
Full textRobberecht, L., F. Chai, M. Dehurtevent, P. Marchandise, T. Bécavin, J. C. Hornez, and E. Deveaux. "A novel anatomical ceramic root canal simulator for endodontic training." European Journal of Dental Education 21, no. 4 (May 5, 2016): e1-e6. http://dx.doi.org/10.1111/eje.12207.
Full textBreimer, Gerben E., Vivek Bodani, Thomas Looi, and James M. Drake. "Design and evaluation of a new synthetic brain simulator for endoscopic third ventriculostomy." Journal of Neurosurgery: Pediatrics 15, no. 1 (January 2015): 82–88. http://dx.doi.org/10.3171/2014.9.peds1447.
Full textPanova, I. A., E. A. Rokotyanskaya, L. A. Sytova, and L. M. Salakhova. "Effectiveness of Using a Uterine Trainer for Teaching Surgical Hemostasis Skills." Virtual Technologies in Medicine 1, no. 3 (September 17, 2021): 161–62. http://dx.doi.org/10.46594/2687-0037_2021_3_1360.
Full textLindquist, Nathan R., Matthew Leach, Matthew C. Simpson, and Jastin L. Antisdel. "Evaluating Simulator-Based Teaching Methods for Endoscopic Sinus Surgery." Ear, Nose & Throat Journal 98, no. 8 (April 24, 2019): 490–95. http://dx.doi.org/10.1177/0145561319844742.
Full textDissertations / Theses on the topic "Anatomical simulator"
Dicko, Ali Hamadi. "Construction of musculoskeletal systems for anatomical simulation." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM084/document.
Full textThe use of virtual humans has spread in various activities in recent years.Beyond virtual surgery, virtual bodies are increasingly used to design medical devices, vehicles, and daily life hardware more generally.They also turn out to be extraordinary supports to learn anatomy.Recent movies (Avatar, Lord of the Rings, etc) demonstrated that anatomy and biomechanics can be used to design high-quality characters.However, reproducing the behavior of anatomical structures remains a complex task, and a great amount and variety of knowledge is necessary for setting up high quality simulations.This makes the modeling of human body for simulation purposes an open problem, a tedious task, but also a fascinating research subject.Through this PhD, we address the problem of the construction of biomechanical models of the musculoskeletal systems for several domains : animation, biomechanics and teaching.Our goal is to simplify the entire process of model design by making it more intuitive and faster.Our approach is to address each difficulty : the representation and use of anatomical knowledge, the geometrical modeling and the efficient simulation of the musculoskeletal system thanks to three novel contributions introduced during these research works.Our first contribution focuses on the biomechanical construction of a hybrid model of lumbar spine.In this work, we show that hybrid approaches that combine both rigid body systems and finite element models allow interactive simulations, accurate, while respecting the principles of anatomy and mechanics.Our second contribution addresses the problem of the complexity of anatomical, physiological and functional knowledge.Based on a novel ontology of anatomical functions of the human body, we introduce a novel pipeline to automatically build models that simulate physiological functions of our bodies.The ontology allows us to extract detailed knowledge using simple queries.The outputs of these queries are used to set up simulation models of the functional aspects as they were formalized and described by anatomists.Finally our third contribution, the anatomy transfer, allows the mapping of available geometrical and mechanical models to the morphology of any specific individual.This novel registration method enables the automatic construction of the internal anatomy of any character defined by his skin, by transferring organs from a reference character.It allows to overcome the need to re-construct these geometries for each new simulation, and it contributes to accelerate the simulations setup for a range of people with different morph
Galdames, Grunberg Francisco José. "Brain magnetic resonance image segmentation for the construction of an anatomical model dedicated to mechanical simulation." Tesis, Universidad de Chile, 2012. http://www.repositorio.uchile.cl/handle/2250/112056.
Full textDurante una neurocirugía se debe contar con información anatómica precisa, la cual es comúnmente obtenida por medio de un registro entre la posición del paciente y datos pre-operatorios. Uno de los principales problemas para realizar este registro es la deformación del cerebro durante la cirugía, fenómeno conocido como Brain Shift. Para solucionar este problema se han creado modelos mecánicos del cerebro, con los cuales es posible aproximar la deformación real. Estos modelos mecánicos requieren un modelo anatómico del paciente, el cual se obtiene, en la mayor parte de los casos, por medio de una segmentación manual o semi-manual. El objetivo de esta tesis es mejorar la obtención del modelo anatómico, proponiendo un método automático para obtener un modelo anatómico del cerebro, adaptado a la anatomía particular del paciente y adecuado para un posterior modelamiento mecánico. El método propuesto realiza una pre-segmentación del cerebro, seguida de una segmentación basada en modelos deformables para identificar las estructuras anatómicas más relevantes para el modelamiento mecánico. Se incluyen las estructuras comúnmente utilizadas en la literatura: superficie cortical, superficie interna del cráneo y ventrículos. Además, se incluyen las membranas internas del cerebro: falx cerebri y tentorium cerebelli. Estas membranas se han incorporado en los modelos de muy pocas publicaciones, aun cuando su importancia es reconocida en la literatura. La segmentación por modelos deformables que se ha implementado está principalmente basada en mallas simplex, las cuales son duales topológicos de las mallas de triángulos. Para aprovechar las cualidades complementarias de estas dos representaciones, se ha desarrollado un nuevo método de transformación entre ellas. Nuestro método usa una interpolación geométrica basada en la distancia a los planos tangentes a los vértices de las mallas. El método de transformación fue evaluado usando mallas estándar y obtuvo excelentes resultados al compararlo con el método actualmente más usado, el cual emplea el centro de gravedad de las caras de las mallas. En nuestro método de segmentación las estructuras son segmentadas de manera secuencial y respetando las relaciones anatómicas entre ellas. La segmentación obtenida fue evaluada empleando las bases de datos en linea más usadas (BrainWeb, IBSR, SVE). La segmentación de cada estructura fue evaluada de manera independiente y se realizaron algunas comparaciones con métodos de segmentación populares y establecidos, obteniendo resultados superiores. Las segmentaciones de la superficie cortical, la superficie interna del cráneo y los ventrículos fueron evaluadas usando los indices de Jaccard (J) y Dice (κ). Los resultados para la superficie cortical fueron: J = 0,904 y κ = 0,950 en BrainWeb; J = 0,902 y κ = 0,948 en IBSR; J = 0,946 y κ = 0,972 en SVE. Los resultados para la superficie interna del cráneo fueron J = 0,945 y κ = 0,972 en BrainWeb. Los resultados para los ventrículos fueron: J = 0,623 y κ = 0,766 en IBSR. Las segmentaciones de las membranas internas del cerebro fueron evaluadas midiendo la distancia entre nuestra segmentación y la posición estimada de las membranas en la base de datos IBSR. La distancia media para el tentorium cerebelli fue 1,673 mm, y para el falx cerebri fue 0,745 mm.
Wilson, Timothy Lyle. "Using MR anatomically simulated normal image to reveal spect finited resolution effects." Thesis, Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/17341.
Full textFischer, Shain Ann. "A Three-Dimensional Anatomically Accurate Finite Element Model for Nerve Fiber Activation Simulation Coupling." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1365.
Full textDiLorenzo, Paul Carmen. "Breathing, laughing, sneezing, coughing model and control of an anatomically inspired, physically-based human torso simulation /." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3350078.
Full textIncludes abstract. Title from first page of PDF file (viewed January 28, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 100-106).
Egger, Robert [Verfasser], and Marcel [Akademischer Betreuer] Oberländer. "Simulation of sensory-evoked signal flow in anatomically realistic models of neural networks / Robert Egger ; Betreuer: Marcel Oberländer." Tübingen : Universitätsbibliothek Tübingen, 2016. http://d-nb.info/1164168851/34.
Full textHao, Guoliang. "Imaging of the atria and cardiac conduction system : from experiment to computer modelling." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/imaging-of-the-atria-and-cardiac-conduction-system--from-experiment-to-computer-modelling(3e5dba52-70f3-4fa8-890d-adfe2380086c).html.
Full textNehring, Wendy M., and Felissa R. Lashley. "Nursing Simulation: A Review of the Past 40 Years." Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etsu-works/6706.
Full textGinsburger, Kévin. "Modeling and simulation of the diffusion MRI signal from human brain white matter to decode its microstructure and produce an anatomic atlas at high fields (3T)." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS158/document.
Full textDiffusion Magnetic Resonance Imaging of water in the brain has proven very useful to establish a cartography of brain connections. It is the only in vivo modality to study anatomical connectivity. A few years ago, it has been shown that diffusion MRI is also a unique tool to perform virtual biopsy of cerebral tissues. However, most of current analytical models (AxCaliber, ActiveAx, CHARMED) employed for the estimation of white matter microstructure rely upon a basic modeling of white matter, with axons represented by simple cylinders and extra-axonal diffusion assumed to be Gaussian. First, a more physically plausible analytical model of the human brain white matter accounting for the time-dependence of the diffusion process in the extra-axonal space was developed for Oscillating Gradient Spin Echo (OGSE) sequence signals. A decoding tool enabling to solve the inverse problem of estimating the parameters of the white matter microstructure from the OGSE-weighted diffusion MRI signal was designed using a robust optimization scheme for parameter estimation. Second, a Big Data approach was designed to further improve the brain microstructure decoding. All the simulation tools necessary to construct computational models of brain tissues were developed in the frame of this thesis. An algorithm creating realistic white matter tissue numerical phantoms based on a spherical meshing of cell shapes was designed, enabling to generate a massive amount of virtual voxels in a computationally efficient way thanks to a GPU-based implementation. An ultra-fast simulation tool of the water molecules diffusion process in those virtual voxels was designed, enabling to generate synthetic diffusion MRI signal for each virtual voxel. A dictionary of virtual voxels containing a huge set of geometrical configurations present in white matter was built. This dictionary contained virtual voxels with varying degrees of axonal beading, a swelling of the axonal membrane which occurs after strokes and other pathologies. The set of synthetic signals and associated geometrical configurations of the corresponding voxels was used as a training data set for a machine learning algorithm designed to decode white matter microstructure from the diffusion MRI signal and estimate the degree of axonal beading. This decoder showed encouraging regression results on unknown simulated data, showing the potential of the presented approach to characterize the microstructure of healthy and injured brain tissues in vivo. The microstructure decoding tools developed during this thesis will in particular be used to characterize white matter tissue microstructural parameters (axonal density, mean axonal diameter, glial density, mean glial cells diameter, microvascular density ) in short and long bundles. The simulation tools developed in the frame of this thesis will enable the construction of a probabilistic atlas of the white matter bundles microstructural parameters, using a mean propagator based diffeomorphic registration tool also designed in the frame of this thesis to register each individual
Perchet, Diane. "Modélisation in-silico des voies aériennes : reconstruction morphologique et simulation fonctionnelle." Phd thesis, Université René Descartes - Paris V, 2005. http://tel.archives-ouvertes.fr/tel-00273244.
Full textDans ce contexte, le projet RNTS RMOD a pour objectif de développer un simulateur morpho-fonctionnel des voies respiratoires pour l'aide au diagnostic, au geste médico-chirurgical et à l'administration de médicaments par inhalation.
Contribuant au projet RMOD, la recherche développée dans cette thèse propose une modélisation in-silico de la structure des voies aériennes supérieures (VAS) et proximales (VAP) à partir d'examens tomodensitométriques (TDM). L'investigation morphologique et la simulation fonctionnelle bénéficient alors de géométries 3D réelles, adaptées au patient et spécifiques des pathologies rencontrées.
La modélisation développée fait coopérer des méthodes originales de segmentation, de construction de surface maillée et d'analyse morpho-fonctionnelle.
La segmentation des VAP est obtenue par un schéma diffusif et agrégatif gouverné par un modèle markovien, dont l'initialisation repose sur l'opérateur de coût de connexion sous contrainte topographique. De cette segmentation, l'axe central de l'arbre bronchique est extrait de manière robuste et précise en combinant information de distance, propagation de fronts, et partition conditionnelle locale. Cet axe central est représenté sous forme d'une structure hiérarchique multivaluée synthétisant caractéristiques topologiques et géométriques de l'arbre bronchique. Une surface maillée est ensuite construite en appliquant une procédure de Marching Cubes adaptative, les paramètres des différents filtres mis en jeu étant automatiquement ajustés aux caractéristiques locales du réseau bronchique conditionnellement aux attributs de l'axe central.
La segmentation des VAS repose sur une propagation markovienne exploitant les variations locales de densité. L'initialisation combine morphologie mathématique et information de contour afin de garantir la robustesse à la topologie. Une procédure de type triangulation de Delaunay restreinte à une surface fournit ensuite la représentation maillée des VAS. Il est établi que la topologie et la géométrie des structures complexes composant les VAS sont effectivement préservées.
Pour permettre aux médecins de valider les modèles maillés ainsi construits, un environnement virtuel 3D convivial et interactif a été réalisé. En outre, la morphologie des voies aériennes exo- et endo-luminale est analysée de façon automatique à partir de simulations d'écoulement pour des géométries réelles.
Enfin, une modélisation unifiée des VAP et VAS est obtenue pour la première fois. Elle démontre la pertinence des approches développées. Elle ouvre la voie à la construction de modèles in-silico complets de l'appareil respiratoire ainsi qu'aux études fonctionnelles prenant en compte les paramètres morphologiques susceptibles d'influer localement ou globalement sur la dynamique des écoulements.
Books on the topic "Anatomical simulator"
Anatomía de un simulacro. Buenos Aires: Editorial Leviatán, 2007.
Find full text1932-, Fujino Toyomi, ed. Simulation and computer-aided surgery. Chichester: Wiley, 1994.
Find full textLambrecht, J. Thomas. 3-D modeling technology in oral and maxillofacial surgery. Chicago: Quintessence Pub. Co., 1995.
Find full textS, Suri Jasjit, and Farag Aly A, eds. Deformable models. New York: Springer, 2007.
Find full textGeorge, Xu Xie, and Eckerman K. F, eds. Handbook of anatomical models for radiation dosimetry. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2010.
Find full textGarg, Amit. Learning anatomy from rotating three dimensional virtual models: Do more views of an anatomical object improve understanding its spatial characteristics? 1998.
Find full text(Editor), Xie George Xu, and Keith F. Eckerman (Editor), eds. Handbook of Anatomical Models for Radiation Dosimetry (Series in Medical Physics and Biomedical Engineering). Taylor & Francis, 2008.
Find full textElkhateb, Rania, and Jill M. Mhyre. Difficult Airway: Special Considerations in Pregnancy. Edited by Matthew D. McEvoy and Cory M. Furse. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190226459.003.0053.
Full textBiomedical Simulation Lecture Notes in Computer Science. Springer, 2010.
Find full textRatib, Osman, Nadia Magnenat-Thalmann, and Hon Fai Choi. 3D Multiscale Physiological Human. Springer, 2014.
Find full textBook chapters on the topic "Anatomical simulator"
Acosta, Eric, and Bharti Temkin. "Build-and-Insert: Anatomical Structure Generation for Surgical Simulators." In Medical Simulation, 230–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25968-8_26.
Full textNoetscher, Gregory, Peter Serano, Ara Nazarian, and Sergey Makarov. "Computational Tool Comprising Visible Human Project® Based Anatomical Female CAD Model and Ansys HFSS/Mechanical® FEM Software for Temperature Rise Prediction Near an Orthopedic Femoral Nail Implant During a 1.5 T MRI Scan." In Brain and Human Body Modelling 2021, 133–51. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15451-5_9.
Full textLloyd, Bryn, Emilio Cherubini, Silvia Farcito, Esra Neufeld, Christian Baumgartner, and Niels Kuster. "Covering Population Variability: Morphing of Computation Anatomical Models." In Simulation and Synthesis in Medical Imaging, 13–22. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46630-9_2.
Full textPlantefève, Rosalie, Nazim Haouchine, Jean-Pierre Radoux, and Stephane Cotin. "Automatic Alignment of Pre and Intraoperative Data Using Anatomical Landmarks for Augmented Laparoscopic Liver Surgery." In Biomedical Simulation, 58–66. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12057-7_7.
Full textLloyd, John E., Antonio Sánchez, Erik Widing, Ian Stavness, Sidney Fels, Siamak Niroomandi, Antoine Perrier, Yohan Payan, and Pascal Perrier. "New Techniques for Combined FEM-Multibody Anatomical Simulation." In Lecture Notes in Computational Vision and Biomechanics, 75–92. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23073-9_6.
Full textChinzei, Kiyoyuki, Takemasa Kawamoto, Takaomi Taira, Hiroshi Iseki, and Kintomo Takakura. "Surgical Simulation in an Anatomical/Functional Atlas with HyperCAS." In Computer-Assisted Neurosurgery, 105–14. Tokyo: Springer Japan, 1997. http://dx.doi.org/10.1007/978-4-431-65889-4_11.
Full textChang, Jun Keun, Chan Young Park, Jongwon Kim, Joo Young Park, Myoung Hee Kim, Byeong Han Lee, Byung Hyun Chung, Dong Chul Han, and Byoung Goo Min. "Anatomical Fitting Simulators (AFS) for Totally Implantable Artificial Heart Design." In Heart Replacement, 353–56. Tokyo: Springer Japan, 1996. http://dx.doi.org/10.1007/978-4-431-67020-9_51.
Full textAudette, Michel A., A. Fuchs, Oliver Astley, Yoshihiko Koseki, and Kiyoyuki Chinzei. "Towards Patient-Specific Anatomical Model Generation for Finite Element-Based Surgical Simulation." In Surgery Simulation and Soft Tissue Modeling, 340–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45015-7_33.
Full textvan der Leeden, R., Eldad J. Avital, and G. Kenyon. "Nasal Airflow in a Realistic Anatomic Geometry." In Direct and Large-Eddy Simulation VI, 423–30. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/978-1-4020-5152-2_49.
Full textSanders, Benjamin, Paul DiLorenzo, Victor Zordan, and Donald Bakal. "Toward Anatomical Simulation for Breath Training in Mind/Body Medicine." In Recent Advances in the 3D Physiological Human, 105–19. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-565-9_7.
Full textConference papers on the topic "Anatomical simulator"
Kuxhaus, Laurel, Patrick J. Schimoler, Jeffrey S. Vipperman, Angela M. Flamm, Daniel Budny, Mark E. Baratz, Patrick J. DeMeo, and Mark Carl Miller. "Measuring Moment Arms Using Closed-Loop Force Control With an Elbow Simulator." In ASME 2007 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2007. http://dx.doi.org/10.1115/sbc2007-176513.
Full textZaitseva, Elena, Miroslav Kvassay, Vitaly Levashenko, Thomas M. Deserno, Victor Voski, and Andreas Herrler. "Qualitative evaluation of faults (mathematical incorrectness) in anatomical model for Regional Anaesthesia Simulator." In 2016 International Conference on Information and Digital Technologies (IDT). IEEE, 2016. http://dx.doi.org/10.1109/dt.2016.7557192.
Full textKurse, Manish, Hod Lipson, and Francisco Valero-Cuevas. "A Fast Simulator to Model Complex Tendon-Bone Interactions: Application to the Tendinous Networks Controlling the Fingers." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206601.
Full textZheng, Fei, WenFeng Lu, Yoke San Wong, and Kelvin Weng Chiong Foong. "GPU-Based Haptic Simulator for Dental Bone Drilling." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47019.
Full textPerosky, Joseph, Abdul Aref, Daniel Westcott, Robert Przybylski, Derek Woodrum, Suzanne Dooley-Hash, and Pamela Andreatta. "A Low-Cost Cricothyroidotomy Trauma Simulator With a Real Time Vital Signs Feedback System." In ASME 2010 5th Frontiers in Biomedical Devices Conference. American Society of Mechanical Engineers, 2010. http://dx.doi.org/10.1115/biomed2010-32078.
Full textSheshadri, Vikram B., Paul J. Rullkoetter, and Ben M. Hillberry. "In Vitro Measurement of the Six Degree-of-Freedom Kinematics of the Human Knee During Simulated Gait." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-0418.
Full textMoncisvalles, E., D. Lorias, A. Minor, and J. Villalobos. "Design and Development of a Gastrointestinal Simulator System with Software That Allows to Find the Anatomical Location and a Flexible Endoscope Emulator." In 2014 IEEE 27th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2014. http://dx.doi.org/10.1109/cbms.2014.117.
Full textChokhandre, Snehal, and Ahmet Erdemir. "A Multiscale Specimen-Specific Data Set to Enable Comprehensive Modeling and Simulation of the Tibiofemoral Joint." In ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fmd2013-16117.
Full textKia, Mohammad, Trent M. Guess, and Antonis Stylianou. "Musculoskeletal Model of the Human Knee With Representation of Menisci During the Stance Phase of a Walk Cycle." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80746.
Full textContijoch, Francisco, Jennifer M. Lynch, David D. Pokrajac, Andrew D. A. Maidment, and Predrag R. Bakic. "Shape analysis of simulated breast anatomical structures." In SPIE Medical Imaging, edited by Norbert J. Pelc, Robert M. Nishikawa, and Bruce R. Whiting. SPIE, 2012. http://dx.doi.org/10.1117/12.912275.
Full text