Deep Learning Based Real-Time Semantic Segmentation of Cerebral Vessels and Cranial Nerves in Microvascular Decompression Scenes
R. F. Bai; X. R. Liu; S. Jiang and H. J. Sun
刊名Cells
2022
卷号11期号:11页码:18
DOI10.3390/cells11111830
英文摘要Automatic extraction of cerebral vessels and cranial nerves has important clinical value in the treatment of trigeminal neuralgia (TGN) and hemifacial spasm (HFS). However, because of the great similarity between different cerebral vessels and between different cranial nerves, it is challenging to segment cerebral vessels and cranial nerves in real time on the basis of true-color microvascular decompression (MVD) images. In this paper, we propose a lightweight, fast semantic segmentation Microvascular Decompression Network (MVDNet) for MVD scenarios which achieves a good trade-off between segmentation accuracy and speed. Specifically, we designed a Light Asymmetric Bottleneck (LAB) module in the encoder to encode context features. A Feature Fusion Module (FFM) was introduced into the decoder to effectively combine high-level semantic features and underlying spatial details. The proposed network has no pretrained model, fewer parameters, and a fast inference speed. Specifically, MVDNet achieved 76.59% mIoU on the MVD test set, has 0.72 M parameters, and has a 137 FPS speed using a single GTX 2080Ti card.
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语种英语
内容类型期刊论文
源URL[http://ir.ciomp.ac.cn/handle/181722/66507]  
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
R. F. Bai,X. R. Liu,S. Jiang and H. J. Sun. Deep Learning Based Real-Time Semantic Segmentation of Cerebral Vessels and Cranial Nerves in Microvascular Decompression Scenes[J]. Cells,2022,11(11):18.
APA R. F. Bai,X. R. Liu,&S. Jiang and H. J. Sun.(2022).Deep Learning Based Real-Time Semantic Segmentation of Cerebral Vessels and Cranial Nerves in Microvascular Decompression Scenes.Cells,11(11),18.
MLA R. F. Bai,et al."Deep Learning Based Real-Time Semantic Segmentation of Cerebral Vessels and Cranial Nerves in Microvascular Decompression Scenes".Cells 11.11(2022):18.
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