ArticleScientific data2025
Spine endoscopic atlas: an open-source dataset for surgical instrument segmentation.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Benchmarking deep learning pipelines for surgical instrument segmentation in endoscopic spine surgery: cross-dataset evaluation under deployment-realistic conditions.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Domain-Adapted Foundation Models for Single-Click Surgical Instrument Segmentation in Spinal Endoscopy.Neurospine · 2026Article
- Spine endoscopic atlas: an open-source dataset for surgical instrument segmentation.Scientific data · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Endoscopic spine surgery (ESS) is a minimally invasive procedure used for spinal nerve decompression, herniated disc removal, and spinal fusion. Despite its many advantages, its steep learning curve poses a challenge to widespread adoption. The development of artificial intelligence (AI) systems is crucial for enhancing the precision and safety of ESS. The automatic segmentation of surgical instruments is a key step towards realizing intelligent surgical assistance systems. As such, this paper has created the Spine Endoscopic Atlas (SEA) dataset, a comprehensive collection of annotated images encompassing all instruments commonly used in spinal endoscopic surgery. In total, SEA contains 48,510 images and 10,662 instrument segmentations derived from real-world ESS. This dataset is specifically designed to train deep learning models for precise instrument segmentation. Through validation of five models, we demonstrate the dataset's value in improving segmentation accuracy under complex conditions, providing a foundation for future AI advancements in ESS.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.