  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.
