Expanded Comprehensive Robotic Cholecystectomy Dataset (CRCD)
In recent years, the application of machine learning to minimally invasive surgery (MIS) has attracted considerable interest. Datasets are critical to the use of such techniques. This paper presents a unique dataset recorded during ex vivo pseudo-cholecystectomy procedures on pig livers using the da...
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Zusammenfassung: | In recent years, the application of machine learning to minimally invasive
surgery (MIS) has attracted considerable interest. Datasets are critical to the
use of such techniques. This paper presents a unique dataset recorded during ex
vivo pseudo-cholecystectomy procedures on pig livers using the da Vinci
Research Kit (dVRK). Unlike existing datasets, it addresses a critical gap by
providing comprehensive kinematic data, recordings of all pedal inputs, and
offers a time-stamped record of the endoscope's movements. This expanded
version also includes segmentation and keypoint annotations of images,
enhancing its utility for computer vision applications.
Contributed by seven surgeons with varied backgrounds and experience levels
that are provided as a part of this expanded version, the dataset is an
important new resource for surgical robotics research. It enables the
development of advanced methods for evaluating surgeon skills, tools for
providing better context awareness, and automation of surgical tasks. Our work
overcomes the limitations of incomplete recordings and imprecise kinematic data
found in other datasets. To demonstrate the potential of the dataset for
advancing automation in surgical robotics, we introduce two models that predict
clutch usage and camera activation, a 3D scene reconstruction example, and the
results from our keypoint and segmentation models. |
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DOI: | 10.48550/arxiv.2412.12238 |