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In the effort to aid cytologic diagnostics by establishing automatic singlecell screening using high throughput digital holographic microscopy forclinical studies thousands of images and millions of cells are captured. Thebottleneck lies in an automatic, fast, and unsupervised segmentation techniquethat does not limit the types of cells which might occur. We propose anunsupervised multistage method that segments correctly without confusing noiseor reflections with cells and without missing cells that also includes thedetection of relevant inner structures, especially the cell nucleus in theunstained cell. In an effort to make the information reasonable andinterpretable for cytopathologists, we also introduce new cytoplasmic andnuclear features of potential help for cytologic diagnoses which exploit thequantitative phase information inherent to the measurement scheme. We show thatthe segmentation provides consistently good results over many experiments onpatient samples in a reasonable per cell analysis time.

Unsupervised high-throughput segmentation of cells and cell nuclei in quantitative phase images