# RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/rasnet-segmentation-for-tracking-surgical-instruments-in-surgical-videos-using/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zhen-Liang Ni,Gui‐Bin Bian,Xiao‐Liang Xie,Zeng‐Guang Hou,Xiao-Hu Zhou,Yan-Jie Zhou |
| Citations | 66 |
| DOI | 10.1109/embc.2019.8856495 |
| Fields | Computer Science,Engineering,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2979328438 |
| PMID | 31947155 |
| Type | conference-paper |
| Year | 2019 |

## Paper authors

- [Xiao-Hu Zhou](https://scholariq.org/researchers/xiao-hu-zhou/)
- [Xiao‐Liang Xie](https://scholariq.org/researchers/xiao-liang-xie/)

## Paper primary topic

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)

## Paper topics

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [Anatomy and Medical Technology](https://scholariq.org/topics/anatomy-and-medical-technology/)
- [Augmented Reality Applications](https://scholariq.org/topics/augmented-reality-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.