In the effort to aid cytologic diagnostics by establishing automatic single
cell screening using high throughput digital holographic microscopy for
clinical studies thousands of images and millions of cells are captured. The
bottleneck lies in an automatic, fast, and unsupervised segmentation technique
that does not limit the types of cells which might occur. We propose an
unsupervised multistage method that segments correctly without confusing noise
or reflections with cells and without missing cells that also includes the
detection of relevant inner structures, especially the cell nucleus in the
unstained cell. In an effort to make the information reasonable and
interpretable for cytopathologists, we also introduce new cytoplasmic and
nuclear features of potential help for cytologic diagnoses which exploit the
quantitative phase information inherent to the measurement scheme. We show that
the segmentation provides consistently good results over many experiments on
patient samples in a reasonable per cell analysis time.

建议使用无人值守的多阶段分割方法进行细胞核的自动、快速、无监督分割，并利用该方法的定量相位信息来介绍新的细胞质和细胞核特征，以提高细胞学诊断的可行性和可解释性。