MISAW-Seg: Pixel-Level Surgical Tool Segmentation for Microsurgical Anastomosis

MISAW-Seg is a surgical segmentation dataset extending the original MISAW dataset with pixel-level annotations for microsurgical tools. It focuses on artificial vessel anastomosis tasks and was developed by KIST-HARILAB. The dataset was last updated on February 10, 2026.

Use Cases

• Train pixel-level segmentation models based on annotated microsurgical tools.
• Develop and evaluate robot-assisted surgery systems based on annotated tool interactions.
• Benchmark computer vision algorithms for surgical scene understanding based on the segmentation annotations.

Strengths

• Dataset provides pixel-level segmentation annotations for microsurgical tools.
• It extends a known dataset (MISAW) for a specific surgical task (artificial vessel anastomosis).
• The dataset is associated with a research paper titled 'Microsurgical Instrument Segmentation for Robot-Assisted Surgery'.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

KIST-HARILAB

Freshness

Last updated 2026-02-10 00:10:07; freshness should be verified.