Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Deep Pyramid Local Attention Neural Network for Cardiac Structure Segmentation in Two-dimensional Echocardiography | |
Fei Liu; Wang K(王坤); Dan Liu; Xin Yang; Jie Tian | |
发表期刊 | Medical Image Analysis |
ISSN | 1361-8415 |
2021 | |
卷号 | 67期号:67页码:101873 |
通讯作者 | Tian, Jie(tian@ieee.org) |
摘要 | Automatic semantic segmentation in 2D echocardiography is vital in clinical practice for assessing vari- ous cardiac functions and improving the diagnosis of cardiac diseases. However, two distinct problems have persisted in automatic segmentation in 2D echocardiography, namely the lack of an effective feature enhancement approach for contextual feature capture and lack of label coherence in category prediction for individual pixels. Therefore, in this study, we propose a deep learning model, called deep pyramid lo- cal attention neural network (PLANet), to improve the segmentation performance of automatic methods in 2D echocardiography. Specifically, we propose a pyramid local attention module to enhance features by capturing supporting information within compact and sparse neighboring contexts. We also propose a label coherence learning mechanism to promote prediction consistency for pixels and their neighbors by guiding the learning with explicit supervision signals. The proposed PLANet was extensively evalu- ated on the dataset of cardiac acquisitions for multi-structure ultrasound segmentation (CAMUS) and sub-EchoNet-Dynamic, which are two large-scale and public 2D echocardiography datasets. The experi- mental results show that PLANet performs better than traditional and deep learning-based segmentation methods on geometrical and clinical metrics. Moreover, PLANet can complete the segmentation of heart structures in 2D echocardiography in real time, indicating a potential to assist cardiologists accurately and efficiently. |
关键词 | 2D echocardiography Cardiac structure segmentation Pyramid local attention Label coherence learning |
DOI | 10.1016/j.media.2020.101873 |
关键词[WOS] | LEFT-VENTRICLE ; LEARNING ARCHITECTURES ; TRACKING ; SEQUENCES ; DIAGNOSIS ; MODELS |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Ministry of Science and Technology of China[2017YFA0205200] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[61671449] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[YJKYYQ20180048] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Chinese Academy of Sciences[XDB32030200] |
项目资助者 | Ministry of Science and Technology of China ; National Natural Science Foundation of China ; Chinese Academy of Sciences |
WOS研究方向 | Computer Science ; Engineering ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000598892100007 |
出版者 | ELSEVIER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41462 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Jie Tian |
推荐引用方式 GB/T 7714 | Fei Liu,Wang K,Dan Liu,et al. Deep Pyramid Local Attention Neural Network for Cardiac Structure Segmentation in Two-dimensional Echocardiography[J]. Medical Image Analysis,2021,67(67):101873. |
APA | Fei Liu,Wang K,Dan Liu,Xin Yang,&Jie Tian.(2021).Deep Pyramid Local Attention Neural Network for Cardiac Structure Segmentation in Two-dimensional Echocardiography.Medical Image Analysis,67(67),101873. |
MLA | Fei Liu,et al."Deep Pyramid Local Attention Neural Network for Cardiac Structure Segmentation in Two-dimensional Echocardiography".Medical Image Analysis 67.67(2021):101873. |
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