斑马鱼体的无监督SAM细分:适用于黑色素分析
Yuan Meng1, Jing-Xuan Zhou1, Yu-Ting Yang1
1School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
Environmental pollution (Barking, Essex : 1987)
|July 2, 2025
概括
这项研究使用了分段任何模型 (SAM) 来准确量化斑马鱼中的黑色素,发现像PTU和α-Arbutin这样的抑制剂可以以剂量依赖的方式降低黑色素合成.
科学领域:
- * 发育生物学 发育生物学
- * 毒理学 毒理学 毒理学
- * 生物医学成像技术
背景情况:
- *斑马鱼是人类健康研究的有价值的模型,因为它们的透明度和遗传相似性.
- *准确的黑色素量化对于评估色素变质障碍治疗和抑制剂疗效至关重要.
- *现有的斑马鱼的黑色素量化方法可能是劳动密集型的,缺乏精度.
研究的目的:
- * 开发一种精确有效的方法来量化斑马鱼中的黑色素.
- * 研究1--2-尿素 (PTU) 和α-Arbutin对黑色素合成的影响.
- * 利用分段任何模型 (SAM) 实现自动化斑马鱼图像细分.
主要方法:
- * 采用分段任何模型 (SAM) 进行斑马鱼的无监督图像分割.
- * 通过SAM实现了高精度 (100%) 在生成斑马鱼身体面具.
- * 通过在细分体面罩中的像素级整合计算的黑色素含量.
主要成果:
- * 通过增加PTU和α-Arbutin度,观察到黑色素合成受到抑制.
- *基于SAM的方法在面具选择中显示出高精度 (96.7%).
- * 拟议的方法提供了与现有技术可比的定量结果.
结论:
- * 分段任何模型 (SAM) 为斑马鱼中的黑色素量化提供了一个精确而高效的工具.
- *这种自动化方法简化了过程,并减少了图像分析中的手动工作.
- *这些发现证实了PTU和α-Arbutin对斑马鱼黑色素合成的抑制作用.
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