CASIA OpenIR  > 脑图谱与类脑智能实验室  > 脑机接口与融合智能
Semi-supervised cerebrovascular segmentation using TOF-MRA images based on label refinement and consistency regularization
Haibin Huang1,2; Yue Cui1,2; Mingxia Shi1; Shan Yu1,2
2024
Conference NameIEEE International Symposium on Biomedical Imaging (ISBI)
Conference Date27-30 May
Conference PlaceAthens, Greece
Abstract

Accurate segmentation of cerebrovascular structures is crucial for scientific research and clinical applications. However, manual labeling of the whole brain’s sophisticated and complex vasculature network is costly and limited, and could potentially compromise the performance and generalizability of supervised model which solely relies on high-quality labels. Semi-supervised strategies have been investigated to effectively take advantage of abundant unlabeled data. In this study, we propose a novel confident learning-based mean-teacher framework (CL-MT), which integrates noisy label refinement to alleviate the adverse effects of label noise and consistency regularization tailored for noisy labeled regions to learn useful representations from unlabeled data. In addition, we propose a backbone model UST-Net, which incorporates convolution and Transformer in both the encoder and decoder. This architecture enables the model to capture long-range dependencies at various scales. Comprehensive experiments demonstrated that our model outperformed state-of-the-art supervised and semi-supervised methods and can be generalized to diverse human and non-human primate datasets.

Sub direction classification医学影像处理与分析
planning direction of the national heavy laboratory其他
Paper associated data
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57473
Collection脑图谱与类脑智能实验室_脑机接口与融合智能
Affiliation1.Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, ChineseAcademy of Sciences, Beijing, China
2.2School of Artificial Intelligence, University of ChineseAcademy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Haibin Huang,Yue Cui,Mingxia Shi,et al. Semi-supervised cerebrovascular segmentation using TOF-MRA images based on label refinement and consistency regularization[C],2024.
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