# Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/tracking-by-detection-of-surgical-instruments-in-minimally-invasive-surgery-via/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zijian Zhao,Sandrine Voros,Ying Weng,Faliang Chang,Ruijian Li |
| Citations | 56 |
| DOI | 10.1080/24699322.2017.1378777 |
| Fields | Computer Science,Engineering,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.tandfonline.com/doi/pdf/10.1080/24699322.2017.1378777?needAccess=true |
| OpenAlex ID | https://openalex.org/W2757977547 |
| PMID | 28937281 |
| Type | article |
| Year | 2017 |

## Paper authors

- [Ying Weng](https://scholariq.org/researchers/ying-weng/)

## Paper primary topic

- [Soft Robotics and Applications](https://scholariq.org/topics/soft-robotics-and-applications/)

## Paper topics

- [Soft Robotics and Applications](https://scholariq.org/topics/soft-robotics-and-applications/)
- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [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.