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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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3D-COSI ~ 3D Collection of Surgical Instruments

Authors: Gijs Luijten; Christina Gsaxner; Jianning Li; Antonio Pepe; Narmada Ambigapathy; Moon Kim; Xiaojun Chen; +4 Authors

3D-COSI ~ 3D Collection of Surgical Instruments

Abstract

COSI - 3D STL Collection of Surgical Instruments Due to large file names, we have chosen to use https://www.7-zip.org/ which is 100% free and compatible with WinZip. If you encounter an error using WinZip, its likely due to large file names, please use 7zip. Inside the repository, you will find an information overview "Overview.docx", a showcase video "Example video 3D instruments.mp4", STL files of 103 surgical instruments "Surgical Instruments.7z", examples of variations of the surgical instruments using Blender add-on or Python script build on the Trimesh library "Blender Part x of 8 ... 7z", or "Trimesh part x of 9 ... .7z". You will also find the used Blender Add On "MultiMesh.zip", measurements of virtual instruments and settings for the add-on (.xlsx), and the script that was used to perform these measurements inside a single folder, "Scripts, measurements and used Blender settings.7z". The proposed data collection consists of 103 3D-scanned medical instruments from the clinical routine, scanned with structured light scanners. The collection consists, for example, of instruments like retractors, forceps, and clamps. The collection is augmented by generating likewise models using 3D software, resulting in an inflated dataset for analysis. The collection can be used for general instrument detection and tracking in operating room settings or a freeform marker-less instrument registration for tool tracking in augmented reality. Furthermore, for medical simulation or training scenarios in virtual reality or mixed reality. The data within this work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0 NC) (https://creativecommons.org/licenses/by-nc/4.0/). Related article:Luijten, G., Gsaxner, C., Li, J. et al. 3D surgical instrument collection for computer vision and extended reality. Sci Data 10, 796 (2023). https://doi.org/10.1038/s41597-023-02684-0

This work was supported by the REACT-EU project KITE (grant number: EFRE-0801977, Plattform für KI-Translation Essen, https://kite.ikim.nrw/), FWF enFaced 2.0 (grant number: KLI-1044, https://enfaced2.ikim.nrw/), and the Clinician Scientist Program of the Faculty of Medicine RWTH Aachen University. Instruments provided by the Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen. The STL files of the surgical instruments are also available within MedShapeNet (https://medshapenet.ikim.nrw).

Keywords

3D collection, Augmented Reality, Surgical instruments, STL, Mixed Reality, Virtual Reality, Structured light scanner, stereolithography, Blender

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
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