XSeed Funding for Needle Guidance

2021-05-05: Together with Dr. Yu Sun and his Advanced Micro and Nanosystems Laboratory (AMNL) at University of Toronto we are an XSeed Winning Recipient of the 2021-23 Funding Competition. We are looking forward to this collaboration with Dr. Vitor Mendes Pereira on an exciting imaging and automation challenge.

100% success with the Canada Graduate Scholarships – Doctoral Program

2021-04-28: The Natural Sciences and Engineering Research Council of Canada (NSERC) has awarded Wenzhi Guo and Mustafa Haiderbhai prestigious scholarships for 3 years each. Congratulations!

$2.8m CFI Funding at SickKids

2021-03-05: We are part of a big push and research effort towards better fetal interventions. Team leaders Dr. James Drake and Dr. Tim Van Mieghem have received funding from the Canada Foundation of Innovation (CFI) to build the research arm of the Ontario Fetal Centre (OFC). We are very happy to buy equipment to assist future fetal interventions through OCT-guidance.

Two abstracts accepted at ImNO 2021

2021-01-15: The two abstracts of Wenzhi Guo and Emily Huang with the titles "Augmented Reality Relaxed Skin Tension Lines for Face Surgery - Initial Results on a Mobile Device" as well as "2D and 3D Labeling Methods for Facial Skin Tension Lines" are accepted for the 19th Annual Imaging Network Ontario Symposium.

Paper accepted at IEEE ISBI 2021

2021-01-08: Haotian Yang's paper "Real-Time Coarse-To-Fine Depth Estimation On Stereo Endoscopic Images With Self-Supervised Learning" was accepted for the IEEE International Symposium on Biomedical Imaging (ISBI) 2021.

Interdisciplinary Work between Computer Science, Engineering and Medicine

Our research is centred around computer and robot assisted medical diagnosis and interventions. We address challenges in the research field of medical technology, that have a focus on optical, spatial, cognitive or manipulative limits.

Computer Vision for Diagnosis and Therapy

Our research is mainly dealing with camera-based procedures, including endoscopic and microscopic vision as well as webcams and volumetric imaging modalities like Optical Coherence Tomography

Medical Robotics

We are using robot simulations and experimental surgical robots like the da Vinci Research Kit (dVRK) or custom-built systems

Artificial Intelligence

We investigate with established and own new datasets, how machine learning and decision making can be applied in the medical domain

Our Team

Team Members

Lueder A. Kahrs

Assistant Professor

Mustafa Haiderbhai

PhD Student CS

Wenzhangzhi (Wenzhi) Guo

PhD Student CS

Radian Gondokaryono

PhD Student CS, starting Fall 2021

Yaniv Khaslavsky

MSc Student CS, starting Fall 2021

Bizhe Bai

Volunteer, ROP CSC399, 2021

Charles Yuan

Volunteer, 2021

Karthik Immaneni

ROP, CSC399, 2021

Justin Regef

ROP, CSC399, 2021

Fangrui Dong

Volunteer, 2021

Mahak Khurmi

Volunteer, 2021

Jinjie Sun

Volunteer, 2021

Waleed Sawan

Volunteer, 2021

Tawseef Hanif

Volunteer, 2021

Omar Farag

Volunteer, 2021

Huizhen Cui

Volunteer, 2021

Likhit Talasila

Volunteer, 2020/21

Mac Martin

ROP, CSC399, 2021

Rajath Subramanyam

ROP, CSC399, 2021

Co-supervised Students & Research Staff

Shamitra Rohan

MScAC Student, University of Toronto

Danting Dong

MScAC Student, University of Toronto

Mona Al-Taha

MASc Student, University of Toronto

Jan Bergmeier

Doctoral Candidate, Leibniz University Hannover, Germany

Jacob F. Fast

Doctoral Candidate, Leibniz University Hannover, Germany

Research Group Alumni

Mansoor Saqib

USRA Summer 2020

Ajitesh Misra

ROP CSC299, 2020

Trevor Nagy

Work-Study & CSC392, 2020

Haotian Yang

ROP CSC499, 2020/21

Jaivir Singh Panesar

ROP CSC499, 2020/21

Maha Kesibi

ROP CSC499, 2020/21

Raiyan Chowdhury

ROP CSC499, 2020/21

Emily Huang

Volunteer, DCS Scholarship, 2020/21

Our Research Projects

  • All
  • Computer Vision
  • Medical Robotics
  • Artificial Intelligence

da Vinci Research Kit


3D Endoscopic Vision


OCT Data Processing


Vision-based Skin Flap Surgery


Soft Tissue Laser Cutting


Vision-based Control of Robots