We report microscopically collected infrared spectra of cells found in human urine in an effort to develop automatic methods for bladder cancer screening. Unsupervised multivariate analysis of the observed spectral patterns reveals distinct spectral classes, which correlated very well with visual cytology. Therefore, we believe that spectral analysis of individual cells can aid cytology in rendering reliable diagnoses based on objective measurements and discriminant algorithms.

中文翻译：

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红外显微光谱细胞学：尿细胞学中细胞类型的自动区分

我们报告了在人类尿液中发现的细胞的显微镜收集红外光谱，以开发膀胱癌筛查的自动方法。观察到的光谱模式的无监督多变量分析揭示了不同的光谱类别，这与视觉细胞学非常相关。因此，我们相信单个细胞的光谱分析可以帮助细胞学基于客观测量和判别算法提供可靠的诊断。