Imaging Analysis and Evaluation of Neural Stem Cell Intracerebral Migration and Functional Reconstruction Based on Deep Learning

Neural stem cell is a type of stem cell with self-renewal ability and multi-directional differentiation potential. Under certain conditions, neural stem cells can differentiate into neurons, oligodendrocytes, and astrocytes, thereby participating in the occurrence of the nervous system. Considering that deep convolutional neural networks have better feature learning capabilities for image data than feedforward neural networks, this paper studies how to apply deep convolutional neural networks to modeling based on imaging features, and constructs convolutional neural networks. In this paper, the distribution of CD133
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neural stem cells in different neuroanatomical regions of rat brain and possible migration flow were studied. The experimental results show that there are obvious differences in the distribution of neural stem cells in different neuroanatomical regions. With the growth and development of rats, a large number of CD133
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neural stem cells migrate from the subventricular zone to the surrounding ganglia, corpus callosum, and cerebral cortex. Seven days before the operation, the rats were trained in water maze, and the EL (Escape Latency) of the rats was recorded for 1 week, 2 weeks and 1 month. Compared with the control group of sham operation, EL was significantly increased in the cerebral ischemia-reperfusion group. Compared with cerebral ischemia-reperfusion + acupuncture group and cerebral ischemia-reperfusion group, EL was significantly smaller. The results show that electroacupuncture can induce the proliferation of newborn cells in the brain and promote the differentiation of newborn cells into glial cells and nerve cells. After electroacupuncture intervention, a small number of new nerve cells already have the activity and function of secreting Ach. Electroacupuncture intervention can promote the recovery of rat nerve function after cerebral ischemia and reperfusion.