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Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures

The monograph written by Ron Alterovitz and Ken Goldberg combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures. A challenge clinicians commonly face is compensating for errors ca...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Alterovitz, Ron (Autor), Goldberg, Ken (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Springer Tracts in Advanced Robotics,
Temas:
Acceso en línea:Texto Completo

MARC

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100 1 |a Alterovitz, Ron.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures  |h [electronic resource] /  |c by Ron Alterovitz, Ken Goldberg. 
250 |a 1st ed. 2008. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2008. 
300 |a XVI, 156 p. 55 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Springer Tracts in Advanced Robotics,  |x 1610-742X 
505 0 |a Physically-Based Simulation of Soft Tissue Deformations -- Motion Planning in Deformable Soft Tissue with Applications to Needle Insertion -- Motion Planning in Deformable Soft Tissue with Obstacles with Applications to Needle Steering -- Motion Planning for Curvature-Constrained Mobile Robots with Applications to Needle Steering -- The Stochastic Motion Roadmap: A Sampling-Based Framework for Planning with Motion Uncertainty -- Motion Planning for Radiation Sources during High-Dose-Rate Brachytherapy -- Conclusion. 
520 |a The monograph written by Ron Alterovitz and Ken Goldberg combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures. A challenge clinicians commonly face is compensating for errors caused by soft tissue deformations that occur when imaging devices or surgical tools physically contact soft tissue. A number of methods are presented which can be applied to a variety of medical procedures, from biopsies to anaesthesia injections to radiation cancer treatment. They can also be extended to address problems outside the context of medical robotics, including nonholonomic motion planning for mobile robots in field or manufacturing environments. . 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Automation. 
650 0 |a Artificial intelligence. 
650 0 |a System theory. 
650 0 |a Control theory. 
650 0 |a Biomedical engineering. 
650 0 |a Image processing-Digital techniques. 
650 0 |a Computer vision. 
650 1 4 |a Control and Systems Theory. 
650 2 4 |a Control, Robotics, Automation. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Systems Theory, Control . 
650 2 4 |a Biomedical Engineering and Bioengineering. 
650 2 4 |a Computer Imaging, Vision, Pattern Recognition and Graphics. 
700 1 |a Goldberg, Ken.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
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830 0 |a Springer Tracts in Advanced Robotics,  |x 1610-742X 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-540-69259-1  |z Texto Completo 
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950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)