ArticleScientific data2025
CholecInstanceSeg: A Tool Instance Segmentation Dataset for Laparoscopic Surgery.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Analysis and mitigation of equipment-induced shortcuts in AI models for laparoscopic cholecystectomy.PLOS digital health · 2026Article
- Grounding surgical action triplets with instrument instance segmentation: a dataset and target-aware fusion approach.International journal of computer assisted radiology and surgery · 2026Article
- ROBUST-MIPS: A Combined Skeletal Pose and Instance Segmentation Dataset for Laparoscopic Surgical Instruments.Scientific data · 2026Article
- Artificial Intelligence in Minimally Invasive and Robotic Gastrointestinal Surgery: Major Applications and Recent Advances.Journal of personalized medicine · 2026Review
- Artificial intelligence analysis of minimally invasive surgery data.Journal of robotic surgery · 2026Review
- Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system.Military Medical Research · 2026Article
- CholecInstanceSeg: A Tool Instance Segmentation Dataset for Laparoscopic Surgery.Scientific data · 2025Article
- SegMatch: semi-supervised surgical instrument segmentation.Scientific reports · 2025Article
- Generalized Few-Shot MM-Former For Surgical Scene Panoptic Segmentation.Healthcare technology lettersArticle
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In laparoscopic and robotic surgery, precise tool instance segmentation is an essential technology for advanced computer-assisted interventions. Although publicly available procedures of routine surgeries exist, they often lack comprehensive annotations for tool instance segmentation. Additionally, the majority of standard datasets for tool segmentation are derived from porcine(pig) surgeries. To address this gap, we introduce CholecInstanceSeg, the largest open-access tool instance segmentation dataset to date. Derived from the existing CholecT50 and Cholec80 datasets, CholecInstanceSeg provides novel annotations for laparoscopic cholecystectomy procedures in patients. Our dataset comprises 41.9k annotated frames extracted from 85 clinical procedures and 64.4k tool instances, each labelled with semantic masks and instance IDs. To ensure the reliability of our annotations, we perform extensive quality control, conduct label agreement statistics, and benchmark the segmentation results with various instance segmentation baselines. CholecInstanceSeg aims to advance the field by offering a comprehensive and high-quality open-access dataset for the development and evaluation of tool instance segmentation algorithms.
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Registered trials
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.