mlsanityData to 14 Oct 2026

hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries

arXiv 2110.12555 ↗First posted 24 Oct 2021cs.CVcited by 7

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Abstract (arXiv)

Automated surgical instrument localization is an important technology to understand the surgical process and in order to analyze them to provide meaningful guidance during surgery or surgical index after surgery to the surgeon. We introduce a new dataset that reflects the kinematic characteristics of surgical instruments for automated surgical instrument localization of surgical videos. The hSDB(hutom Surgery DataBase)-instrument dataset consists of instrument localization information from 24 cases of laparoscopic cholecystecomy and 24 cases of robotic gastrectomy. Localization information for all instruments is provided in the form of a bounding box for object detection. To handle class imbalance problem between instruments, synthesized instruments modeled in Unity for 3D models are included as training data. Besides, for 3D instrument data, a polygon annotation is provided to enable instance segmentation of the tool. To reflect the kinematic characteristics of all instruments, they are annotated with head and body parts for laparoscopic instruments, and with head, wrist, and body parts for robotic instruments separately. Annotation data of assistive tools (specimen bag, needle, etc.) that are frequently used for surgery are also included. Moreover, we provide statistical information on the hSDB-instrument dataset and the baseline localization performances of the object detection networks trained by the MMDetection library and resulting analyses.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 23 of its 29 references that are in the map. First posted on arXiv 24 Oct 2021.

Builds on

23 of 29 references.

References · 23

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11 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 4; 2026: 1.

7 papers.

  1. 2025Scaling up self-supervised learning for improved surgical foundation modelscited by 25
  2. 2025EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-trainingcited by 11
  3. 2023Whether and When does Endoscopy Domain Pretraining Make Sense?cited by 8
  4. 2024Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer Visioncited by 7
  5. 2025Surgical Foundation Model Leveraging Compression and Entropy Maximization for Image-Guided Surgical Assistancecited by 0
  6. 2025XiCAD: Camera Activation Detection in the Da Vinci Xi User Interfacecited by 0
  7. 2026LD-RSVIS: A Large-Scale and Diverse Benchmark for Referring Surgical Video Instrument Segmentationcited by 0