A new large-scale 4K video dataset was created for supermicrosurgical training and robot development.
A large 4 K dataset of supermicrosurgical anastomosis at the 0.2 mm scale.
Jing Liang et al. · Scientific data · 2026
Background
Supermicrosurgery, involving vessels smaller than 0.8 mm, is an important emerging field in reconstructive surgery.
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Results
hours
extensive video duration in the new dataset for delicate surgery training
n = 452 procedures
More results
Its development is limited by the lack of suitable training resources and the current performance of microsurgical robotic systems.
Here, we present the Microsurgical Silicone Tube Anastomosis dataset (MSTA), a large-scale 4 K video dataset of 0.2-mm silicone tube anastomosis procedures.
More results
The participants represented a wide range of experience levels, with completion times ranging from 125 to 600 seconds, providing a broad spectrum of technical performance for analysis.
In addition, the dataset contains 47,452 segmentation annotation surgical frames, supporting computer vision studies.
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Conclusion
Its scale and standardized design provide a reliable basis for building intelligent assistance systems and establishing benchmarks for skill evaluation in supermicrosurgery.