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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Alterovitz, Ron (Συγγραφέας), Goldberg, Ken (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
Σειρά:Springer Tracts in Advanced Robotics, 50
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Alterovitz, Ron.  |e author. 
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. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2008. 
300 |a XVI, 156 p. 55 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Springer Tracts in Advanced Robotics,  |x 1610-7438 ;  |v 50 
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 Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Computer graphics. 
650 0 |a System theory. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Mechatronics. 
650 0 |a Biomedical engineering. 
650 1 4 |a Engineering. 
650 2 4 |a Control. 
650 2 4 |a Control, Robotics, Mechatronics. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Systems Theory, Control. 
650 2 4 |a Biomedical Engineering. 
650 2 4 |a Computer Imaging, Vision, Pattern Recognition and Graphics. 
700 1 |a Goldberg, Ken.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783540692577 
830 0 |a Springer Tracts in Advanced Robotics,  |x 1610-7438 ;  |v 50 
856 4 0 |u http://dx.doi.org/10.1007/978-3-540-69259-1  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)