Semantic segmentation of pyramidal neuron skeletons using geometric deep learning

被引:1
作者
Li, Lanlan [1 ]
Qi, Jing [1 ]
Geng, Yi [1 ]
Wu, Jingpeng [2 ]
机构
[1] Fuzhou Univ, Coll Phys & Informat Engn, Fujian Key Lab Intelligent Proc & Wireless Transmi, Fuzhou 350116, Fujian, Peoples R China
[2] Flatiron Inst, Ctr Computat Neurosci, New York, NY 10010 USA
基金
中国国家自然科学基金;
关键词
Pyramidal neuron; geometric deep learning; neuron skeleton; semantic segmentation; point cloud;
D O I
10.1142/S1793545823400060
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Neurons can be abstractly represented as skeletons due to the filament nature of neurites. With the rapid development of imaging and image analysis techniques, an increasing amount of neuron skeleton data is being produced. In some scientific studies, it is necessary to dissect the axons and dendrites, which is typically done manually and is both tedious and time-consuming. To automate this process, we have developed a method that relies solely on neuronal skeletons using Geometric Deep Learning (GDL). We demonstrate the effectiveness of this method using pyramidal neurons in mammalian brains, and the results are promising for its application in neuroscience studies.
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页数:8
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