2019-05-16T10:57:30 n15305

Robot-assisted minimally invasive orthopedic procedures

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The dataset contains multimedia recorded on cadaver and phantom (plastic model) tissue in relation to the PhD thesis "Robust and dense Visual SLAM for robot-assisted minimally invasive orthopedic procedures". Related publications can be consulted here.

The dataset contains timestamped recordings of two video sources (arthroscopic camera and external camera), robotic motion data and motion capture data. The data can be used to develop and evaluate assistive systems and algorithms (e.g. SLAM, SfM, visual servoing) for challenging minimally invasive orthopedic procedures.

Data file types include .png images and .txt files for calibration and ground truth data.

The related PhD thesis developed a vision-based robotic surgical assistant for minimally invasive orthopedic procedures. The system is composed of a robotic arm with an attached camera-arthroscope bundle for intra-articular navigation. The system is capable of a) localizing instruments robustly and reliably inside the human joints and b) generating dense and accurate 3D reconstructed models of the knee joint from intra-articular images. Thanks to these capabilities the system would allow for the semi-autonomous navigaton of the camera (via visual servoing) to follow the surgeons’ tools.

Data acquisition was approved by the Australian National Health and Medical Research Council (NHMRC) – Registered Committee Number EC00171 under Approval Number 1400000856.

Access rights

Prior to downloading data files, the owner of this dataset asks that users email the dataset contact to indicate their name, contact email, research institution (if applicable) and intended use of the data.

Geographical area of data collection

kmlPolyCoords
153.022299,-27.386877
kmlPolyCoords
153.027368,-27.477474

Publications

Dense-ArthroSLAM: Dense intra-articular 3D reconstruction with robust localization prior for arthroscopy https://eprints.qut.edu.au/124147/
ArthroSLAM: Multi-sensor robust visual localization for minimally invasive orthopedic surgery https://eprints.qut.edu.au/124134/
Evaluation of keypoint detectors and descriptors in arthroscopic images for feature-based matching applications https://eprints.qut.edu.au/108170/

Research areas

SLAM
Medical robots and systems
Minimally invasive procedures
Minimally invasive surgery
Computer vision for medical robotics
Arthroscopy
Orthopedics
Medical robotics

Cite this collection

Marmol, Andres; Peynot, Thierry (2019): Robot-assisted minimally invasive orthopedic procedures. Queensland University of Technology. (Dataset) https://doi.org/10.25912/5c661cc47e1f7

Related information

Australian Centre for Robotic Vision - Resources Hub https://resources.rvhub.org/robotic-arthroscopy/

Partner institution

QUT's Medical and Healthcare Robotics Group https://research.qut.edu.au/ras/research/medical-robotics/

Licence


Creative Commons Attribution-NonCommercial-Share Alike 4.0 (CC-BY-NC-SA)
http://creativecommons.org/licenses/by-nc-sa/4.0/

Copyright

© COPYRIGHT 2019, AUSTRALIAN CENTRE FOR ROBOTIC VISION. ALL RIGHTS RESERVED.

Dates of data collection

From 2015-03-23 to 2019-03-23

Connections

Has association with
Anjali Tumkur Jaiprakash  (Researcher)
Jonathan Roberts  (Researcher)
Peter Corke  (Researcher)
Ross Crawford  (Researcher)
Thierry Peynot  (Researcher)
Has chief investigator
Andres Marmol  (Researcher)

Contacts

Name: Dr. Thierry Peynot
Phone: 07 3138 6903

Other

Date record created:
2019-01-18T15:21:12
Date record modified:
2019-05-16T10:57:30
Record status:
Published - Open Access