Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery

doi:10.1016/j.bspc.2023.105434

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 生物识别与安全技术研究中心

	Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery
	Wu, Zhiying 4; Lau, Chun Yin 4; Zhou, Qianang 2; Wu, Jinlin 3,4; Wang, Yuxi 4; Liu, Qifeng 4; Lei, Zhen 3,4; Liu, Hongbin 1,3,4
刊名	BIOMEDICAL SIGNAL PROCESSING AND CONTROL
	2024
卷号	87 页码:10
关键词	Transformer Semi-supervised segmentation Structural similarity Surgical instrument segmentation
ISSN号	1746-8094
DOI	10.1016/j.bspc.2023.105434
通讯作者	Liu, Hongbin(liuhongbin@ia.ac.cn)
英文摘要	Precise instrument segmentation helps tracking of instruments in surgery. The most of the existing instrument segmentation methods are fully supervised, which are based on 100% labeled data. However, the annotation for instrument segmentation are really expensive, which need the skilled professionals who can identify the parts and types of the surgical instruments. In this work, we propose a transformer-based semi-supervised instrument segmentation for endoscopic surgery, called Surgivisor. First, we present a data augmentation technique to generate synthetic data from endoscopic images to overcome the complex background and instrument collision problem, by fully using the information of unlabeled data and pseudo labels. Second, we propose a mutual prototype loss and a dual structural similarity loss to address illumination reflection and bloody condition issues in the training phase. With the two improvements, the effectiveness of proposed method is validated by the experiments on EndoVis Challenges. It exceeds the state-of-the-art results on the sub-tasks of binary, part, and type.
资助项目	InnoHK program
WOS关键词	AGGREGATION ; SIMILARITY ; NETWORK
WOS研究方向	Engineering
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:001086726200001
资助机构	InnoHK program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54319]
专题	自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心
通讯作者	Liu, Hongbin
作者单位	1.Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England 2.Univ Sci & Technol China, Hefei, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China 4.Chinese Acad Sci, Ctr Artificial Intelligence & Robot, Hong Kong Inst Sci & Innovat, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Wu, Zhiying,Lau, Chun Yin,Zhou, Qianang,et al. Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery[J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL,2024,87:10.
APA	Wu, Zhiying.,Lau, Chun Yin.,Zhou, Qianang.,Wu, Jinlin.,Wang, Yuxi.,...&Liu, Hongbin.(2024).Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery.BIOMEDICAL SIGNAL PROCESSING AND CONTROL,87,10.
MLA	Wu, Zhiying,et al."Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery".BIOMEDICAL SIGNAL PROCESSING AND CONTROL 87(2024):10.