High throughput quantitative phase imaging show immense potential for clinical applications in various disease detection, however, traditional interferometric setups on optical benchtops are bulky and expensive by design. We present a low-cost, compact interferometric chamber system that would consist of merely three lenses and one beam splitter. The presented system can provide high throughput single-cell level screening of million cell sample population. In combination with customized dataset refinement algorithm and machine learning, we developed a novel technique that would allow for detection of RBC morphology-altering diseases such as sickle cell disease.
Disorder strength is a metric that is used to measure cell stiffness. Through calculating disorder strength from cell phase images reconstructed from various QPI systems, we have discovered that this parameter differs by system used for acquisition. With our model, we demonstrate that disorder strength is highly dependent on image resolution. When corrected with our simulation model, disorder strength measurements from different QPI systems can be directly compared and enable cross-system analysis. Cell disorder strength infers important biophysical information on cellular stiffness of normal cells, carcinogen-exposed cells, and cancer cells.
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