GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation

• URL: http://arxiv.org/abs/2309.11144v1
• Date: Wed, 20 Sep 2023 08:43:40 GMT
• Title: GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
• Authors: Ziyang Zheng, Jiewen Yang, Xinpeng Ding, Xiaowei Xu, Xiaomeng Li
• Abstract summary: We propose a novel Gobal-Local fusion (GL-Fusion) network to jointly utilize multi-view information globally and locally. A Multi-view Global-based Fusion Module (MGFM) is proposed to extract global context information. A Multi-view Local-based Fusion Module (MLFM) is designed to extract correlations of cardiac structures from different views.
• Score: 15.8851111502473
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cardiac structure segmentation from echocardiogram videos plays a crucial role in diagnosing heart disease. The combination of multi-view echocardiogram data is essential to enhance the accuracy and robustness of automated methods. However, due to the visual disparity of the data, deriving cross-view context information remains a challenging task, and unsophisticated fusion strategies can even lower performance. In this study, we propose a novel Gobal-Local fusion (GL-Fusion) network to jointly utilize multi-view information globally and locally that improve the accuracy of echocardiogram analysis. Specifically, a Multi-view Global-based Fusion Module (MGFM) is proposed to extract global context information and to explore the cyclic relationship of different heartbeat cycles in an echocardiogram video. Additionally, a Multi-view Local-based Fusion Module (MLFM) is designed to extract correlations of cardiac structures from different views. Furthermore, we collect a multi-view echocardiogram video dataset (MvEVD) to evaluate our method. Our method achieves an 82.29% average dice score, which demonstrates a 7.83% improvement over the baseline method, and outperforms other existing state-of-the-art methods. To our knowledge, this is the first exploration of a multi-view method for echocardiogram video segmentation. Code available at: https://github.com/xmed-lab/GL-Fusion

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