CASIA OpenIR  > 中国科学院分子影像重点实验室
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
Source PublicationMedical Image Analysis
ISSN1361-8415
2021
Volume67Issue:67Pages:101873
Corresponding AuthorTian, Jie(tian@ieee.org)
Abstract

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.

Keyword2D echocardiography Cardiac structure segmentation Pyramid local attention Label coherence learning
DOI10.1016/j.media.2020.101873
WOS KeywordLEFT-VENTRICLE ; LEARNING ARCHITECTURES ; TRACKING ; SEQUENCES ; DIAGNOSIS ; MODELS
Indexed BySCI
Language英语
Funding ProjectMinistry 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]
Funding OrganizationMinistry of Science and Technology of China ; National Natural Science Foundation of China ; Chinese Academy of Sciences
WOS Research AreaComputer Science ; Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000598892100007
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/41462
Collection中国科学院分子影像重点实验室
Corresponding AuthorJie Tian
Recommended Citation
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.
Files in This Item: Download All
File Name/Size DocType Version Access License
online public versio(3848KB)期刊论文出版稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Fei Liu]'s Articles
[Wang K(王坤)]'s Articles
[Dan Liu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Fei Liu]'s Articles
[Wang K(王坤)]'s Articles
[Dan Liu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Fei Liu]'s Articles
[Wang K(王坤)]'s Articles
[Dan Liu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: online public version.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.