Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories
文献类型：会议论文
| 作者 | Yi Zeng(曾毅) ; Weida Bi(毕韦达); Xuan Tang(唐璇); Bo Xu(徐波)
|
| 出版日期 | 2014 |
| 会议名称 | The 2014 International Conference on Brain Informatics and Health (BIH 2014) |
| 会议日期 | August 11-14 |
| 会议地点 | Warsaw, Poland |
| 关键词 | Neuron Morphology Reconstruction Neuronal Morphology Modeling Soma Reconstruction |
| 卷号 | 8609 |
| 页码 | 1-11 |
| 英文摘要 | Neuronal morphology modeling is one of the key steps for reverse engineering the brain at the micro level. It creates a realistic digital version of the neuron obtained by microscopy reconstruction in a visualized way so that the structure of the whole neuron (including soma, dendrite, axon, spin, etc.) is visible in different angles in a three dimensional space. Whether the modeled neuronal morphology matches the original neuron in vivo is closely related to the details captured by the manually sampled morphological points. Many data in public neuronal morphology data repositories (such as the NeuroMorpho project) focus more on the morphology of dendrites and axons, while there are only a few points to represent the neuron soma. The lack of enough details for neuron soma makes the modeling on the soma morphology a challenging task. In this paper, we provide a general method to neuronal morphology modeling (including the soma and its connections to surrounding dendrites, and axons, with a focus on how different components are connected) and handle the challenging task when there are not many detailed sample points for soma. |
| 收录类别 | EI |
| 会议录 | Lecture Notes in Artificial Intelligence
 |
| 会议录出版者 | Springer |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10356]  |
| 专题 | 类脑智能研究中心_类脑认知计算 |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Yi Zeng,Weida Bi,Xuan Tang,et al. Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories[C]. 见:The 2014 International Conference on Brain Informatics and Health (BIH 2014). Warsaw, Poland. August 11-14. |
入库方式： OAI收割
来源：自动化研究所
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