8 citations · 10 across the 4 of their papers we have counts for
4 papers
Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks
Ji Woong Kim, Tony Z. Zhao, Samuel Schmidgall +4
We explore whether surgical manipulation tasks can be learned on the da Vinci robot via imitation learning. However, the da Vinci system presents unique challenges which hinder str…
General surgery vision transformer: A video pre-trained foundation model for general surgery
Samuel Schmidgall, Ji Woong Kim, Jeffrey Jopling +1
The absence of openly accessible data and specialized foundation models is a major barrier for computational research in surgery. Toward this, (i) we open-source the largest datase…
Shape Manipulation of Bevel-Tip Needles for Prostate Biopsy Procedures: A Comparison of Two Resolved-Rate Controllers
Yanzhou Wang, Lidia Al-Zogbi, Jiawei Liu +6
Prostate cancer diagnosis continues to encounter challenges, often due to imprecise needle placement in standard biopsies. Several control strategies have been developed to compens…
General-purpose foundation models for increased autonomy in robot-assisted surgery
Samuel Schmidgall, Ji Woong Kim, Alan Kuntz +2
The dominant paradigm for end-to-end robot learning focuses on optimizing task-specific objectives that solve a single robotic problem such as picking up an object or reaching a ta…