对比三种模型在三维脑细胞图像中定位中心点的精度与差异。

Seeing Cells Clearly: Evaluating Machine Vision Strategies for Microglia Centroid Detection in 3D Images

• 使用ilastik、3D Morph和Omnipose三种工具检测微胶质细胞中心点
• 不同工具对同一图像的检测结果存在显著差异，影响后续分析
• 研究结果提示选择模型需考虑数据特征和下游任务需求

微胶质细胞是大脑中重要的细胞类型，其形态可反映脑健康状况。本研究测试了三种工具——ilastik、3D Morph 和 Omnipose——在三维显微图像中检测微胶质细胞中心点的性能。通过比较各工具的检测效果，发现每种方法对细胞的识别方式不同，这种差异会直接影响从图像中提取的信息质量。研究揭示了模型选择对结果解释的重要影响，强调在生物图像分析中需根据具体任务谨慎选用工具。

原文摘要 · Abstract (English)

Microglia are important cells in the brain, and their shape can tell us a lot about brain health. In this project, I test three different tools for finding the center points of microglia in 3D microscope images. The tools include ilastik, 3D Morph, and Omnipose. I look at how well each one finds the cells and how their results compare. My findings show that each tool sees the cells in its own way, and this can affect the kind of information we get from the images.

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