Cropped single instrument frames subset from Cholec80 [Data set]

  • This dataset is a subset of the original Cholec80 dataset and is used by the OpenMIBOOD framework to evaluate a specific out-of-distribution setting. When using this dataset, it is mandatory to cite the corresponding publication (OpenMIBOOD) and to follow the acknowledgement and citation requirements of the original dataset (Cholec80). The original Cholec80 dataset (associated paper,Homepage)This dataset is a subset of the original Cholec80 dataset and is used by the OpenMIBOOD framework to evaluate a specific out-of-distribution setting. When using this dataset, it is mandatory to cite the corresponding publication (OpenMIBOOD) and to follow the acknowledgement and citation requirements of the original dataset (Cholec80). The original Cholec80 dataset (associated paper,Homepage) consists of 80 cholecystectomy surgery videos recorded at 25 fps, performed by 13 surgeons. It includes phase annotations (25 fps) and tool presence labels (1 fps), with phase definitions provided by a senior surgeon. A tool is considered present if at least half of its tip is visible. The dataset categorizes tools into seven types: Grasper, Bipolar, Hook, Scissors, Clipper, Irrigator, and Specimen bag. Multiple tools may be present in each frame. Additionally, 76 of the 80 videos exhibit a strong black vignette. For this dataset subset, frames were extracted based on tool presence labels, selecting only those containing Grasper, Bipolar, Hook, or Clipper while ensuring that only a single tool appears per frame. To enhance visual consistency, the black vignette was removed by extracting an inner rectangular region, where applicable.show moreshow less

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Metadaten
Author:Max GutbrodORCiD, David RauberOTHORCiD, Danilo Weber NunesORCiD, Christoph PalmOTHORCiDGND
DOI:https://doi.org/10.5281/zenodo.14921670
Document Type:Research Data
Language:English
Year of first Publication:2025
Release Date:2026/02/16
Tag:Cholecystectomy; Deep Learning; Laparoscopic; Out-Of-Distribution Detection; Tool Presence Detection
Note:
Related works
Is derived from
Journal article: 10.1109/TMI.2016.2593957

Software Repository URL 
https://github.com/remic-othr/OpenMIBOOD
file format:.png
file size:20.5 GB
file type:Image
Institutes:Fakultät Informatik und Mathematik
Research Center of Biomedical Engineering - RCBE
Research Center of Health Sciences and Technology - RCHST
Research Center for Artificial Intelligence - RCAI
Fakultät Informatik und Mathematik / Labor Regensburg Medical Image Computing (ReMIC)
DFG subject classification:Ingenieurwissenschaften
research focus:Gesundheit und Soziales
Licence (German):Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell - Weitergabe unter gleichen Bedingungen 4.0 International
Frontdoor-URL:https://opus4.kobv.de/opus4-oth-regensburg/8881
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