Evidence map›Paper›PMID 36128019›Full record

ArticleIEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation2022

ColibriDoc: An Eye-in-Hand Autonomous Trocar Docking System.

Shervin Dehghani, Michael Sommersperger, Junjie Yang, Mehrdad Salehi, Benjamin Busam, Kai Huang, Peter Gehlbach, Iulian Iordachita, Nassir Navab, M Ali Nasseri

Open access · greenAbstract read
In one paragraph

Article in IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 18 citations in OpenAlex.

  1. Evaluation of (Shared) Autonomy in Robot-Assisted Vitreoretinal Surgery Using a Surgical Model.The international journal of medical robotics + computer assisted surgery : MRCAS · 2025
    Article
  2. Extra-abdominal trocar and instrument detection for enhanced surgical workflow understanding.International journal of computer assisted radiology and surgery · 2024
    Article
  3. Article
  4. Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 3 countries.

Shervin DehghaniDepartment of Computer Science in Technische Universität München, München 85748 Germany.
Michael SommerspergerDepartment of Computer Science in Technische Universität München, München 85748 Germany.
Junjie YangAugenklinik und Poliklinik, Klinikum rechts der Isar der Technische Universität München, München 81675 Germany.
Mehrdad SalehiDepartment of Computer Science in Technische Universität München, München 85748 Germany.
Benjamin BusamDepartment of Computer Science in Technische Universität München, München 85748 Germany.
Kai HuangKey Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University), Guangzhou, China.
Peter GehlbachWilmer Eye Institute, Johns Hopkins Hospital, Baltimore, MD, USA.
Iulian IordachitaLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Nassir NavabFull professor and head of the Chair for Computer Aided Medical Procedures Augmented Reality, Technical University of Munich, 85748 Munich, Germany, and an adjunct professor at the Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
M Ali NasseriDepartment of Computer Science in Technische Universität München, München 85748 Germany.
Johns Hopkins University · USJohns Hopkins Hospital · USKlinikum rechts der Isar · DESun Yat-sen University · CNTechnical University of Munich · DE

Funding

Enabling technology for image-guided robot-assisted sub-retinal injectionsR01EB025883 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI IORDACHITA, IULIAN IOAN · 2019 to 2021
$1.5M
NIBIB NIH HHS R01 EB025883
6 · The paper itself

Abstract

Retinal surgery is a complex medical procedure that requires exceptional expertise and dexterity. For this purpose, several robotic platforms are currently under development to enable or improve the outcome of microsurgical tasks. Since the control of such robots is often designed for navigation inside the eye in proximity to the retina, successful trocar docking and insertion of the instrument into the eye represents an additional cognitive effort, and is therefore one of the open challenges in robotic retinal surgery. For this purpose, we present a platform for autonomous trocar docking that combines computer vision and a robotic setup. Inspired by the Cuban Colibri (hummingbird) aligning its beak to a flower using only vision, we mount a camera onto the endeffector of a robotic system. By estimating the position and pose of the trocar, the robot is able to autonomously align and navigate the instrument towards the Trocar Entry Point (TEP) and finally perform the insertion. Our experiments show that the proposed method is able to accurately estimate the position and pose of the trocar and achieve repeatable autonomous docking. The aim of this work is to reduce the complexity of the robotic setup prior to the surgical task and therefore, increase the intuitiveness of the system integration into clinical workflow.

Indexed as

Computer Vision for Medical RoboticsMedical Robots and SystemsPlanningSurgical Robotics

Identifiers

PMID36128019
PMCPMC9484558
OpenAlexW3215643866

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.