Knowledge Commons of Institute of Automation,CAS
An Effective Encoder-Decoder Network for Neural Cell Bodies and Cell Nucleus Segmentation of EM Images | |
Jiang Yi1; Xiao Chi1; Li Linlin1; Shen Lijun1; Chen Xi1; Han Hua2,3,4 | |
2019-07 | |
会议名称 | In2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
页码 | 6302-6305 |
会议日期 | 2019-7 |
会议地点 | 德国柏林 |
会议举办国 | 德国 |
出版者 | IEEE |
产权排序 | 1 |
摘要 | Neural systems are complicated networks connected by a large number of neurons through gap junctions and synapses. At present, for electron microscopy connectomics research, neuron structure recognition algorithms mostly focus on synapses, dendrites, axons and mitochondria, etc. However, effective methods for automatic recognition of neuronal cell bodies are rare. In this paper, we proposed an effective encoder-decoder network, which extracted segmentation features of neural cell bodies and cell nuclei by the modified residual network and pyramid module. The framework is capable of merging multi-scale contextual information and generating efficient segmentation results by integrating multilevel features. We applied this proposed network on two segmentation tasks for electron microscope (EM) images and compared it with other promising methods as U-Net and deeplab v3+. The results demonstrated that our method achieved state-of-the-art performance on quality metrics. Finally, we visualized two intact neural cell bodies and cell nuclei to provide a close look into these fine structures. |
关键词 | Encoder-Decoder Electron Microscopy Neural Cell Bodies Cell Nucleus Image Segmentation |
学科领域 | 计算机科学技术 ; 人工智能 |
学科门类 | 工学::控制科学与工程 |
DOI | 10.1109/EMBC.2019.8857887 |
收录类别 | EI |
资助项目 | Strategic Priority Research Program of Chinese Academy of Science[XDB32030200] ; Special Program of Beijing Municipal Science & Technology Commission[Z181100000118002] ; National Science Foundation of China[61701497] ; National Science Foundation of China[61673381] ; Scientific Research Instrument and Equipment Development Project of the CAS[YZ201671] |
语种 | 英语 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48521 |
专题 | 脑图谱与类脑智能实验室_微观重建与智能分析 |
通讯作者 | Han Hua |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. 3.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China. 4.School of Future technology, University of Chinese Academy of Sciences, Beijing 101408, China. |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Jiang Yi,Xiao Chi,Li Linlin,et al. An Effective Encoder-Decoder Network for Neural Cell Bodies and Cell Nucleus Segmentation of EM Images[C]:IEEE,2019:6302-6305. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
An Effective Encoder(6217KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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