Abstract
The Cell-CT™ platform images cells in 3D with isometric, sub-micron resolution and measures orientation invariant 3D features in each cell. The Cell-CT is being used to identify abnormal pulmonary epithelial cells in sputum to indicate early-stage lung cancer. Sputum also contains pulmonary macrophages that ingest inhaled contaminants from smoking. We hypothesize that the Cell-CT with machine learning would discover subtle phenotypic characteristics in macrophages to differentiate current and never smokers.
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