Overview of automated sickle cell disease diagnosis by analysis of spatio-temporal cell dynamics in digital holographic microscopy

摘要

We overview a previously reported system for automated diagnosis of sickle cell disease based on red blood cell (RBC)membrane fluctuations measured via digital holographic microscopy. A low-cost, compact, 3D-printed shearinginterferometer is used to record video holograms of RBCs. Each hologram frame is reconstructed in order to form aspatio-temporal data cube from which features regarding membrane fluctuations are extracted. The motility-basedfeatures are combined with static morphology-based cell features and inputted into a random forest classifier whichoutputs the disease state of the cell with high accuracy.