Path planning for minimally-invasive knee surgery using a hybrid optimization procedure

Abstract The aim of this study was to develop a procedure for medical tool path planning in minimally-invasive knee surgery. The collision-free paths for the tool were obtained using the control locations method with a hybrid optimization strategy. The tool and knee elements were described with surface meshes. The knee model allowed for bones displacement and variable incision size and location. The proposed procedure was proven to be effective in path planning for minimally-invasive surgery. It can serve as a valuable aid in surgery planning and may also be used in systems for autonomous or semi-autonomous knee surgery.

[1]  Mansoor Davoodi Monfared,et al.  Multi-objective path planning in discrete space , 2013, Appl. Soft Comput..

[2]  Ingo Wald,et al.  Ray tracing deformable scenes using dynamic bounding volume hierarchies , 2007, TOGS.

[3]  Ron Alterovitz,et al.  Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images , 2014, Int. J. Robotics Res..

[4]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[5]  Jean-Michel Renders,et al.  Hybrid methods using genetic algorithms for global optimization , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[6]  A Sarti,et al.  Validation of new soft tissue software in orthognathic surgery planning. , 2011, International journal of oral and maxillofacial surgery.

[7]  Nima Najmaei,et al.  Image‐guided techniques in renal and hepatic interventions , 2013, The international journal of medical robotics + computer assisted surgery : MRCAS.

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  Vicente Mata,et al.  Evolutionary indirect approach to solving trajectory planning problem for industrial robots operating in workspaces with obstacles , 2013 .

[10]  Steven M. LaValle,et al.  RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[11]  Jong Hyeon Park,et al.  Trajectory optimization with GA and control for quadruped robots , 2009 .

[12]  K. M. Deliparaschos,et al.  Evolution of autonomous and semi‐autonomous robotic surgical systems: a review of the literature , 2011, The international journal of medical robotics + computer assisted surgery : MRCAS.

[13]  Miguel A. Vega-Rodríguez,et al.  MOSFLA-MRPP: Multi-Objective Shuffled Frog-Leaping Algorithm applied to Mobile Robot Path Planning , 2015, Eng. Appl. Artif. Intell..

[14]  Yasar Ayaz,et al.  Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments , 2015, Robotics Auton. Syst..

[15]  Y. Petit,et al.  Biomechanical modelling of segmental instrumentation for surgical correction of 3D spinal deformities using Euler-Bernoulli thin-beam elastic deformation equations , 2004, Medical and Biological Engineering and Computing.

[16]  Jerzy W. Rozenblit,et al.  An optimal motion planning method for computer-assisted surgical training , 2014, Appl. Soft Comput..

[17]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[18]  S. Hushek,et al.  3D path planning for virtual endoscopy , 2005 .

[19]  Tomas Akenine-Möller,et al.  A Fast Triangle-Triangle Intersection Test , 1997, J. Graphics, GPU, & Game Tools.

[20]  M. Zuk,et al.  Image-guided bone resection as a prospective alternative to cutting templates—A preliminary study. , 2015, Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery.

[21]  Karl A. Sillay,et al.  Wide-bore 1.5T MRI-guided deep brain stimulation surgery: initial experience and technique comparison , 2014, Clinical Neurology and Neurosurgery.

[22]  James E. Baker,et al.  Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[23]  Leif Kobbelt,et al.  Character animation from 2D pictures and 3D motion data , 2007, TOGS.

[24]  Giuseppe Carbone,et al.  Collision free trajectory planning for hybrid manipulators , 2012 .

[25]  Francisco Herrera,et al.  Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis , 1998, Artificial Intelligence Review.