papers

Publications (10)

cs.CV2021

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…

cs.CV2020

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…

cs.CV2019

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…

cs.CV2017

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…

cs.CV2026

SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation

John J. Han, Adam Schmidt, Max Allan +2

The SCARED dataset is a widely used benchmark for endoscopic depth estimation, offering ground-truth 3D reconstructions captured with a structured light sensor. However, the depth…

cs.CV2018

Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery

Sebastian Bodenstedt, Max Allan, Anthony Agustinos +17

Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking sys…

cs.CV2020

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…

cs.CV2020

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…

cs.RO2021

Learning Invariant Representation of Tasks for Robust Surgical State Estimation

Yidan Qin, Max Allan, Yisong Yue +2

Surgical state estimators in robot-assisted surgery (RAS) - especially those trained via learning techniques - rely heavily on datasets that capture surgeon actions in laboratory o…

cs.CV2024

Online 3D reconstruction and dense tracking in endoscopic videos

Michel Hayoz, Christopher Hahne, Thomas Kurmann +5

3D scene reconstruction from stereo endoscopic video data is crucial for advancing surgical interventions. In this work, we present an online framework for online, dense 3D scene r…