Final Program

9:00 – 9:10 Workshop overview and introduction (organizers)
9:10 – 9:35 From Imaging to Automation

Image-guidance in medical robotics
Tim Salcudean, University of British Columbia

9:35 – 10:00 Short presentations by research groups
10:00 – 10:30 Coffee break with discussions and poster presentations
10:30 – 10:55 From Imaging to Automation (cont)

A neurosurgical robotic ecosystem based on integrated imaging
Ferdinando Rodriguez y Baena, Imperial College London

11:00 – 11:50 Interaction and Dexterity

Increasing Autonomy for Steerable Medical Robots
Ron Alterovitz, UNC Chapel Hill

Human-robot interaction towards image-guided robotics
Jindong Liu, Hamlyn Centre, Imperial College London

11:50 – 12:30 Panel Discussion – How will imaging and interaction paradigms impact new automatized robotic systems in medicine?
12:45 – 13:45 Lunch break
13:45 – 14:45 Bringing Innovation from Bench to Bedside

Automation in robotic surgery through integrated imaging
Azad Shademan, Intuitive Surgical

Imaging technologies in the OR – A newcomer’s perspective on needs and challenges
Pablo Garcia, Verb Surgical

Researching a cognitive approach to robotics imaging
Marco Rocchetto, Konica Minolta Laboratory Europe

 14:45 – 16:00 Panel – A bright future? Perspectives on innovation in imaging medical robotics
16:00 – 16:30 Coffee break with discussions and poster presentations
16:30 – 17:20 Medical Robotics for Image-Based Interventions

Improving cardiovascular interventions using robotics and machine learning
Su-Lin Lee, Hamlyn Centre, Imperial College London

Micro-robotic surgery using visual servoing in OCT
Brahim Tamadazte, FEMTO-ST

17:20 – 17:30 Feedback and outlook – How to foster interaction between research communities & Closing remarks (organizers)

 

Research presentations

  • Pedro A. Patlan-Rosales and Alexandre Krupa
    A general framework for automatic robotic palpation
  • Rebecca Smith, John O’Neill and Timothy M. Kowalewski
    3D Bioprinting Directly Onto Unpredictably-Moving Human Anatomy: Can Dynamic Vision Sensors Improve Performance?
  • L. C. García-Peraza Herrera, W. Li, L. Fidon, C. Gruijthuijsen, A. Devreker, G. Attilakos, J. Deprest, E. Vander Poorten, D. Stoyanov, T. Vercauteren, and S. Ourselin
    ToolNet: Holistically-Nested  Real-Time Segmentation of  Robotic Surgical Tools
  • Kartik Patath, Rangaprasad Arun Srivatsan, Nico Zevallos and Howie Choset
    Dynamic Texture Mapping of 3D models for Stiffness Map Visualization
  • Seongbo Shim, Hyunseok Choi, Daekeun Ji, Wongin Kang, and Jaesung Hong
    Vision Guided Robotic System for Bone Drilling Based on Rolling Friction
  • Fangde Liu, Thomas Watts, Yike Guo, and Ferdinando Rodriguez Y Baena
    Ultrasound Based Localization of a Biologically Inspired Steerable Needle via Convolution Neural Network
  • K. Rabenorosoa, Y. Baran, G. J. Laurent, P. Rougeot, N. Andreff, and B. Tamadazte
    Towards High Accuracy OCT-based Position Control of a Concentric Tube Robot
  • Dimitri Schreiber, Alexander Norbash, Michael Yip
    MRI guided hyper-redundant biopsy robot
  • B. Haydar, B. Tamadazte, N. Andreff, and A. Bartoli
    3D OCT image compression using shearlet transform