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Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Micropatterning and Assembly of 3D Microvessels
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微容器分类的生成神经框架

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    此摘要是机器生成的。

    通过融合本地和全球血管信息,AV-Net改善了视网膜动脉/静脉分类. 这提高了识别与全身疾病相关的血管异常的准确性.

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    科学领域:

    • 眼科医生 眼科 眼科
    • 医疗成像医学成像
    • 人工智能的人工智能

    背景情况:

    • 视网膜血管异常与系统性,心血管和脑血管疾病相关.
    • 准确的视网膜动脉/静脉 (A/V) 分类对于临床决策至关重要.
    • 目前的方法在与非均的亮度,容器厚度变化,分叉和终点作斗争.

    研究的目的:

    • 提出AV-Net,一个新的深度学习模型,用于精确的视网膜动脉/静脉分类.
    • 为了解决处理复杂船舶特征的现有方法的局限性.

    主要方法:

    • AV-Net利用上下文信息和数据融合来改进A/V分类.
    • 一个专门的模块将本地和全球船舶信息融合在一起,生成重量地图.
    • 这种重量图限制了动脉/静脉特征,抑制了背景噪声,并增强了在分叉和终点上的区域提取.
    • 一个多尺度特征模块捕捉了船只的粗细细细节,以提高模型的强度.

    主要成果:

    • 拟议的AV-Net在视网膜动脉/静脉分类方面表现出更高的精度.
    • 在船舶的分叉点和终点实现了增强的特征提取.
    • 通过多尺度特征捕获,模型的稳定性得到了提高.

    结论:

    • AV-Net提供了一个强大的解决方案,用于准确的视网膜动脉/静脉分类.
    • 该模型能够处理复杂的血管形态,从而提高其在诊断相关系统性疾病方面的临床实用性.