118 citations · 211 across the 6 of their papers we have counts for
6 papers · 1 filter
Stereo Correspondence and Reconstruction of Endoscopic Data Challenge
Max Allan, Jonathan Mcleod, Congcong Wang +21
The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform…
daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery
Yidan Qin, Seyedshams Feyzabadi, Max Allan +2
This paper presents a technique to concurrently and jointly predict the future trajectories of surgical instruments and the future state(s) of surgical subtasks in robot-assisted s…
Temporal Segmentation of Surgical Sub-tasks through Deep Learning with Multiple Data Sources
Yidan Qin, Sahba Aghajani Pedram, Seyedshams Feyzabadi +4
Many tasks in robot-assisted surgeries (RAS) can be represented by finite-state machines (FSMs), where each state represents either an action (such as picking up a needle) or an ob…
2018 Robotic Scene Segmentation Challenge
Max Allan, Satoshi Kondo, Sebastian Bodenstedt +38
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward ki…
2017 Robotic Instrument Segmentation Challenge
Max Allan, Alex Shvets, Thomas Kurmann +16
In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand t…
Deep Residual Learning for Instrument Segmentation in Robotic Surgery
Daniil Pakhomov, Vittal Premachandran, Max Allan +2
Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery. In the majority of cases, the…