Multi-level feature aggregation network for instrument identification of endoscopic images-Reference-Cited by-同舟云学术

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Multi-level feature aggregation network for instrument identification of endoscopic images

Published:2020-08-31 Issue:16 Volume:65 Page:165004
ISSN:1361-6560
Container-title:Physics in Medicine & Biology
language:
Short-container-title:Phys. Med. Biol.

Author:

Chu Yakui,Yang Xilin,Li Heng,Ai Danni,Ding Yuan,Fan Jingfan,Song Hong,Yang Jian^ORCID

Funder

National Science and Technology Major Project of China

National Key Research and Development Program of China

National Science Foundation Program of China

Publisher

IOP Publishing

Subject

Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

https://iopscience.iop.org/article/10.1088/1361-6560/ab8dda/pdf

Reference46 articles.

1. Monitoring tool usage in surgery videos using boosted convolutional and recurrent neural networks

2. 3-D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery

3. Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]

4. Surgical tool segmentation using a hybrid deep CNN-RNN auto encoder-decoder

5. Vision-based and marker-less surgical tool detection and tracking: a review of the literature

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3. CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection;Health Information Science and Systems;2023-11-27

4. Future Perspectives of Deep Learning in Laparoscopic Tool Detection, Classification, and Segmentation: A Systematic Review;2023 IEEE 11th International Conference on Serious Games and Applications for Health (SeGAH);2023-08-28

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