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ConUDiff: diffusion model with contrastive pretraining and uncertain region optimization for segmentation of left ventricle from echocardiography

文献类型：期刊论文

作者Zhang, Guohuan2; Zhang, Lei2; Fu, Xuetong2; Wang, Yuanquan2; Zhou, Shoujun1; Wei, Jin3; Zhao, Di4
刊名PATTERN ANALYSIS AND APPLICATIONS
出版日期2025-09-01
卷号28期号:3页码:11
关键词Diffusion models Echocardiography Left ventricle Segmentation Contrastive learning Uncertain region optimization
ISSN号1433-7541
DOI10.1007/s10044-025-01509-7
英文摘要Accurate segmentation of the left ventricle (LV) in echocardiograms plays a crucial role in the diagnosis and treatment of cardiovascular diseases. However, manual segmentation of the left ventricle is time-consuming and subject to inter-observer variability. It is crucial to develop an accurate and automatic segmentation method. In this paper, we propose a novel diffusion-based model, called ConUDiff in short, for LV segmentation in echocardiography. The proposed ConUDiff is based on the denoising diffusion probabilistic model and two modules are introduced, i.e., a contrastive pretrained ResNet-50 encoder and an uncertain region optimization module (UROM). The contrastive pretrained ResNet-50 encoder is employed to extract rich feature representations from the original image and enhance the semantic information contained in the feature maps. The UROM module is designed to optimize uncertain regions in the feature maps. We evaluate our method on two public datasets, i.e., the EchoNet-Dynamic dataset and the EchoNet-Pediatric dataset. The experimental results demonstrate that the proposed ConUDiff outperforms some popular networks, achieving a Dice score of 92.68% on the EchoNet-Dynamic dataset and a Dice score of 90.69% on the EchoNet-Pediatric dataset. Our method shows the potential for echocardiographic left ventricle segmentation.
资助项目the National Science Foundation of China[61976241] ; the National Science Foundation of China[81827805] ; National Science Foundation of China (NSFC)[2018YFA0704102] ; National key R&D program of China[JCYJ20200109114610201] ; Basic Research Project of Shenzhen Science and Technology Innovation Commission
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001514383900001
出版者SPRINGER
源URL[http://119.78.100.204/handle/2XEOYT63/42285]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Wang, Yuanquan; Zhou, Shoujun
作者单位1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
2.Hebei Univ Technol HeBUT, Sch Artificial Intelligence, Tianjin 300401, Peoples R China
3.Third Cent Hosp Tianjin, Tianjin 300171, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Guohuan,Zhang, Lei,Fu, Xuetong,et al. ConUDiff: diffusion model with contrastive pretraining and uncertain region optimization for segmentation of left ventricle from echocardiography[J]. PATTERN ANALYSIS AND APPLICATIONS,2025,28(3):11.
APA Zhang, Guohuan.,Zhang, Lei.,Fu, Xuetong.,Wang, Yuanquan.,Zhou, Shoujun.,...&Zhao, Di.(2025).ConUDiff: diffusion model with contrastive pretraining and uncertain region optimization for segmentation of left ventricle from echocardiography.PATTERN ANALYSIS AND APPLICATIONS,28(3),11.
MLA Zhang, Guohuan,et al."ConUDiff: diffusion model with contrastive pretraining and uncertain region optimization for segmentation of left ventricle from echocardiography".PATTERN ANALYSIS AND APPLICATIONS 28.3(2025):11.

入库方式： OAI收割

来源：计算技术研究所

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