Automated cell identification with 3D optical imaging

Abstract

In this keynote address paper, we overview recently published works on the current techniques and methods for automated cell identification with 3D optical imaging using compact and field portable systems. 3D imaging systems including digital holographic microscopy systems as well as lensless pseudorandom phase encoding systems are capable of capturing 3D information of microscopic objects such as biological cells which allows for highly accurate automated cell identification. Systems based on digital holography enable reconstruction of the cell’s 3D optical path length profile. The reconstructed 3D profiles can be used to extract morphological and spatio-temporal cell features from biological samples for classification and cell identification. Similarly, pseudorandom encoding techniques such as single random phase encoding (SRPE) and double random phase encoding (DRPE) can be used to encode 3D cell information into opto-biological signatures which can be used for cell identification tasks. Recent advancements in these areas are presented including compact and field-portable 3D-printed shearing digital holographic microscopy systems, integration of digital holographic microscopy with head mounted augmented reality devices, and the use of spatio-temporal features extracted from cell membrane fluctuations for sickle cell disease diagnosis.