Overview of cell motility-based sickle cell disease diagnostic system in shearing digital holographic microscopy

Abstract

Abstract We overview a previously reported low-cost, compact, and 3D-printed shearing interferometer system for automated diagnosis of sickle cell disease based on red blood cell (RBC) bio-physical parameters and membrane fluctuations measured via digital holographic microscopy. The portable quantitative phase microscope is used to distinguish between healthy RBCs and those affected by sickle cell disease. Video holograms of RBCs are recorded, then each video hologram frame is computationally reconstructed to retrieve the time-varying phase profile of the cell distribution under study. The dynamic behavior of the cells is captured by creating a spatio-temporal data cube from which features regarding membrane fluctuations are extracted. Furthermore, the Optical Flow algorithm was used to capture lateral motility information of the cells. The motility-based features are combined with physical, morphology-based cell features and inputted into a random forest classifier which outputs the health state of the cell. Classification is performed with high accuracy at both the cell level and patient level.