Development and validation of a deep learning-based laparoscopic system for improving video quality-Reference-Cited by-同舟云学术

Development and validation of a deep learning-based laparoscopic system for improving video quality

Published:2022-10-15 Issue:2 Volume:18 Page:257-268
ISSN:1861-6429
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Zheng Qingyuan^ORCID,Yang Rui,Ni Xinmiao,Yang Song,Jiang Zhengyu,Wang Lei,Chen Zhiyuan,Liu Xiuheng^ORCID

Funder

Hubei Province Key Research and Development Project of China

the Ministry of Education Industry-University Cooperation and Collaborative Education Project of China

the National Medical Education Development Center Medical Simulation Education Research Project of China

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11548-022-02777-y.pdf

Reference47 articles.

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3. Lawrentschuk N, Fleshner NE, Bolton DM (2010) Laparoscopic lens fogging: a review of etiology and methods to maintain a clear visual field. J Endourol 24:905–913

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