Leveraging Surgical Activity Grammar for Primary Intention Prediction in Laparoscopy Procedures
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916591480864768 |
|---|---|
| author | Zhang, Jie Zhou, Song Wang, Yiwei Wan, Chidan Zhao, Huan Cai, Xiong Ding, Han |
| author_facet | Zhang, Jie Zhou, Song Wang, Yiwei Wan, Chidan Zhao, Huan Cai, Xiong Ding, Han |
| contents | Surgical procedures are inherently complex and dynamic, with intricate dependencies and various execution paths. Accurate identification of the intentions behind critical actions, referred to as Primary Intentions (PIs), is crucial to understanding and planning the procedure. This paper presents a novel framework that advances PI recognition in instructional videos by combining top-down grammatical structure with bottom-up visual cues. The grammatical structure is based on a rich corpus of surgical procedures, offering a hierarchical perspective on surgical activities. A grammar parser, utilizing the surgical activity grammar, processes visual data obtained from laparoscopic images through surgical action detectors, ensuring a more precise interpretation of the visual information. Experimental results on the benchmark dataset demonstrate that our method outperforms existing surgical activity detectors that rely solely on visual features. Our research provides a promising foundation for developing advanced robotic surgical systems with enhanced planning and automation capabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_19579 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Leveraging Surgical Activity Grammar for Primary Intention Prediction in Laparoscopy Procedures Zhang, Jie Zhou, Song Wang, Yiwei Wan, Chidan Zhao, Huan Cai, Xiong Ding, Han Robotics Surgical procedures are inherently complex and dynamic, with intricate dependencies and various execution paths. Accurate identification of the intentions behind critical actions, referred to as Primary Intentions (PIs), is crucial to understanding and planning the procedure. This paper presents a novel framework that advances PI recognition in instructional videos by combining top-down grammatical structure with bottom-up visual cues. The grammatical structure is based on a rich corpus of surgical procedures, offering a hierarchical perspective on surgical activities. A grammar parser, utilizing the surgical activity grammar, processes visual data obtained from laparoscopic images through surgical action detectors, ensuring a more precise interpretation of the visual information. Experimental results on the benchmark dataset demonstrate that our method outperforms existing surgical activity detectors that rely solely on visual features. Our research provides a promising foundation for developing advanced robotic surgical systems with enhanced planning and automation capabilities. |
| title | Leveraging Surgical Activity Grammar for Primary Intention Prediction in Laparoscopy Procedures |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.19579 |