Surgical Visual Understanding (SurgVU) Dataset

Aneeq Zia, Max Berniker, Rogerio Nespolo, Conor Perreault, Ziheng Wang +5 more
1/16/2025
cs.CV

No confident code implementation found for this paper.

Abstract

Owing to recent advances in machine learning and the ability to harvest large amounts of data during robotic-assisted surgeries, surgical data science is ripe for foundational work. We present a large dataset of surgical videos and their accompanying labels for this purpose. We describe how the data was collected and some of its unique attributes. Multiple example problems are outlined. Although the dataset was curated for a particular set of scientific challenges (in an accompanying paper), it is general enough to be used for a broad range machine learning questions. Our hope is that this dataset exposes the larger machine learning community to the challenging problems within surgical data science, and becomes a touchstone for future research. The videos are available at https://storage.googleapis.com/isi-surgvu/surgvu24_videos_only.zip, the labels at https://storage.googleapis.com/isi-surgvu/surgvu24_labels_updated_v2.zip, and a validation set for tool detection problem at https://storage.googleapis.com/isi-surgvu/cat1_test_set_public.zip.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{zia2025surgical,
  title  = {Surgical Visual Understanding (SurgVU) Dataset},
  author = {Aneeq Zia and Max Berniker and Rogerio Nespolo and Conor Perreault and Ziheng Wang and Benjamin Mueller and Ryan Schmidt and Kiran Bhattacharyya and Xi Liu and Anthony Jarc},
  year   = {2025},
  eprint = {2501.09209},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.09209v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2501.09209.svg)](https://codeofpaper.com/paper/2501.09209)

Discussion