Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision

doi:10.1109/TNNLS.2023.3315271

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 > 三维可视计算

	Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision
	Wang, Changwei 3,4; Xu, Rongtao 3,4; Xu, Shibiao 2; Meng, Weiliang 3,4; Xiao, Jun 1; Zhang, Xiaopeng 3,4
刊名	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2023-10-12
页码	13
关键词	Detailed representation transfer lung nodules segmentation medical images segmentation soft mask
ISSN号	2162-237X
DOI	10.1109/TNNLS.2023.3315271
通讯作者	Xu, Shibiao(shibiaoxu@bupt.edu.cn) ; Meng, Weiliang(weiliang.meng@ia.ac.cn)
英文摘要	Accurate lung lesion segmentation from computed tomography (CT) images is crucial to the analysis and diagnosis of lung diseases, such as COVID-19 and lung cancer. However, the smallness and variety of lung nodules and the lack of high-quality labeling make the accurate lung nodule segmentation difficult. To address these issues, we first introduce a novel segmentation mask named "soft mask", which has richer and more accurate edge details description and better visualization, and develop a universal automatic soft mask annotation pipeline to deal with different datasets correspondingly. Then, a novel network with detailed representation transfer and soft mask supervision (DSNet) is proposed to process the input low-resolution images of lung nodules into high-quality segmentation results. Our DSNet contains a special detailed representation transfer module (DRTM) for reconstructing the detailed representation to alleviate the small size of lung nodules images and an adversarial training framework with soft mask for further improving the accuracy of segmentation. Extensive experiments validate that our DSNet outperforms other state-of-the-art methods for accurate lung nodule segmentation, and has strong generalization ability in other accurate medical segmentation tasks with competitive results. Besides, we provide a new challenging lung nodules segmentation dataset for further studies (https://drive.google.com/file/d/15NNkvDTb_0Ku0IoPsNMHezJR TH1Oi1wm/view?usp=sharing).
资助项目	National Key Research and Development Program of China[2020YFC2008500] ; National Key Research and Development Program of China[2020YFC2008503] ; National Natural Science Foundation of China[62271074] ; National Natural Science Foundation of China[61972459] ; National Natural Science Foundation of China[62171321] ; National Natural Science Foundation of China[62376271] ; National Natural Science Foundation of China[62365014] ; National Natural Science Foundation of China[52175493] ; National Natural Science Foundation of China[62171157]
WOS关键词	SMALL PULMONARY NODULES ; CT ; ALGORITHMS
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001085429500001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54349]
专题	模式识别国家重点实验室_三维可视计算
通讯作者	Xu, Shibiao; Meng, Weiliang
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Changwei,Xu, Rongtao,Xu, Shibiao,et al. Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2023:13.
APA	Wang, Changwei,Xu, Rongtao,Xu, Shibiao,Meng, Weiliang,Xiao, Jun,&Zhang, Xiaopeng.(2023).Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,13.
MLA	Wang, Changwei,et al."Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023):13.