Detection, identification and tracking of biological micro/nano organisms by computational 3D optical imaging

In this paper we present an overview of our work on a method to provide three-dimensional (3D) identification and tracking of biological micro/nano-organisms. This approach connects digital holographic microscopy and statistical methods for cell identification. For 3D data acquisition of living biological microorganisms, a filtered white light source, LED or laser diode beam propagates through a biological microorganism and the transversely and longitudinally magnified Gabor hologram pattern of the biological microorganism by microscope objective is optically recorded with a CCD camera interfaced with a computer. 3D imaging of the biological microorganism from the magnified Gabor hologram pattern is obtained by applying the computational Fresnel propagation algorithm. For identification and tracking of the biological microorganism, statistical approaches based on statistical estimation and inference algorithms are developed to the segmented holographic 3D image. Overviews of analytical frameworks are discussed and experimental results are presented.