Ron Alterovitz

Ron Alterovitz

Ph.D., University of California, Berkeley

NIH Postdoctoral Research Fellow

Department of Electrical Engineering & Computer Sciences, UC Berkeley

UCSF Comprehensive Cancer Center, UC San Francisco

E-mail: 

ronalt

@

berkeley.edu


My research bridges motion planning algorithms and biomedical informatics, combining ideas from robotics, physically-based simulation, and optimization theory to provide novel computational solutions to problems in medicine and biology, from optimally guiding surgical instruments to clinical targets at the tissue scale to predicting protein motions at the molecular scale.

I am currently an NIH Postdoctoral Research Fellow with the UC Berkeley EECS Department and the UCSF Comprehensive Cancer Center, and I am actively collaborating with researchers at UC Berkeley, UCSF, The Johns Hopkins University, and LAAS-CNRS in Toulouse, France. I earned my doctorate from UC Berkeley in 2006 in Industrial Engineering and Operations Research with minors in Computer Science and Bioengineering, and I earned my B.S. degree with Honors from Caltech in 2001 studying Computer Science. My Ph.D. thesis, completed with advisor Ken Goldberg in the Berkeley Automation Sciences Lab, introduced new motion planning and optimization algorithms for image-guided medical procedures and will be published in an upcoming book by Springer. I have funded my research through multi-year fellowships and grants from NSF, DOD, and NIH.


Curriculum Vitae | Current Research | Publications and Talks | Internet Links


Current Research


Stochastic Motion Roadmaps for Planning with Motion Uncertainty

Motion Planning under Uncertainty: The Stochastic Motion Roadmap

The Stochastic Motion Roadmap (SMR) is a new framework for motion planning that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a goal. The method combines a sampling-based roadmap representation of the configuration space with Markov Decision Processes and Dynamic Programming. Resulting plans are more likely to succeed than deterministic shortest path plans, particularly in biomedical applications like medical needle steering in which uncertainty in motion is high.

Needle Insertion Simulation

Motion Planning in Deformable Tissues

Medical procedures such as biopsies, anesthesia injections, and brachytherapy require inserting a needle to a target inside soft tissue. These procedures are prone to significant error due to tissue deformations caused by the needle. My method to compensate for soft tissue deformations by combining efficient finite element models with a motion planning algorithm was selected as a Best Paper Award Finalist in the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems.


Motion Planning for Steerable Medical Needles

Motion Planning for Steerable Medical Needles

I developed a motion planning algorithm that optimizes motion plans for mobile robots that follow constant-curvature paths and whose response to actions is not fully predictable. I applied this planner to a new class of highly flexible bevel-tip needles (patent pending) that can be steered to targets in soft tissue previously inaccessible to traditional needles. This method, based on Markov Decision Processes and Dynamic Programming along with geometric discretization, has been generalized into the SMR framework.

MR Image

Medical Image Registration for Deformable Tissues

Emerging advances in medical imaging are revolutionizing cancer diagnosis and treatment, and physicians need better software tools to analyze these new images. To register diagnostic images with treatment planning images, I developed an image registration algorithm that explicitly considers soft tissue deformations using a finite element model and estimates uncertain tissue parameters using nonlinear optimization. Results for prostate cancer patient cases indicate a statistically significant improvement over past methods.


Selected Publications

  1. Ron Alterovitz, Thierry Siméon, and Ken Goldberg, "The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty," in Proc. Robotics: Science and Systems, Jun. 2007. (Download PDF)
  2. Ron Alterovitz, Michael Branicky, and Ken Goldberg, "Constant-Curvature Motion Planning Under Uncertainty with Applications in Image-Guided Medical Needle Steering," in Proc. Workshop on the Algorithmic Foundations of Robotics, Jul. 2006. (Download PDF)
  3. Ron Alterovitz, Etienne Lessard, Jean Pouliot, I-Chow Joe Hsu, James F. O'Brien, and Ken Goldberg, "Optimization of HDR brachytherapy dose distributions using linear programming with penalty costs," Medical Physics, vol. 33, no. 11, pp. 4012-4019, Nov. 2006. (Download PDF)
  4. Ron Alterovitz, Ken Goldberg, Jean Pouliot, I-Chow Joe Hsu, Yongbok Kim, Susan Moyher Noworolski, and John Kurhanewicz, "Registration of MR prostate images with biomechanical modeling and nonlinear parameter estimation," Medical Physics, vol. 33, no. 2, pp. 446-454, Feb. 2006. (Download PDF)
  5. Ron Alterovitz, Andrew Lim, Ken Goldberg, Gregory S. Chirikjian, and Allison M. Okamura, "Steering Flexible Needles Under Markov Motion Uncertainty," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Aug. 2005, pp. 120-125. (Download PDF)
  6. Ron Alterovitz, Ken Goldberg, and Allison Okamura, "Planning for Steerable Bevel-tip Needle Insertion Through 2D Soft Tissue with Obstacles," in Proc. IEEE International Conference on Robotics and Automation (ICRA), Apr. 2005, pp. 1652-1657. (Download PDF)
  7. Ron Alterovitz, Ken Goldberg, John Kurhanewicz, Jean Pouliot, I-Chow Hsu, "Image Registration for Prostate MR Spectroscopy Using Biomechanical Modeling and Optimization of Force and Stiffness Parameters," in Proc. 26th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBS), Sept. 2004, pp. 1722-1725. (Download PDF)
  8. Ron Alterovitz, Jean Pouliot, Richard Taschereau, I-Chow Joe Hsu, and Ken Goldberg, "Sensorless Planning for Medical Needle Insertion Procedures," in Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), Oct. 2003, pp. 3337-3343. (Download PDF) (Best Paper Award Finalist)
  9. Ron Alterovitz, Jean Pouliot, Richard Taschereau, I-Chow Joe Hsu, and Ken Goldberg, "Needle Insertion and Radioactive Seed Implantation in Human Tissues: Simulation and Sensitivity Analysis," in Proceedings of the 2003 IEEE International Conference on Robotics and Automation (ICRA 2003), Sept. 2003, pp. 1793-1799. (Download PDF)
  10. Ron Alterovitz, Jean Pouliot, Richard Taschereau, I-Chow Joe Hsu, and Ken Goldberg, "Simulating Needle Insertion and Radioactive Seed Implantation for Prostate Brachytherapy," in Medicine Meets Virtual Reality 11 (MMVR11), J.D. Westwood et al. (Eds.), IOS Press, Jan. 2003, pp. 19-25. (Download PDF)

Complete list of publications


Internet Links