The dynamic properties of subcellular organism are important biomarkers of health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism, and moreover, testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motions by using eigen decomposition (ED) based variance analysis of time-dependent complex optical coherence tomography (OCT) signals. This method reveals superior contrast to noise advantage compared with intensity-based dynamic imaging regime. Further validation experiments were performed with B-mode imaging sections crossing a wide range of sampling frequencies, and on the patterned samples of yeast powder mixed with gelatin/TiO2-water solution. In addition, the proposed method was further used to image mouse cerebral cortex in vivo, suggesting the promising of ED based correlation power mapping in analyzing coupled dynamics of neuron activity and cerebral blood flow. The proposed technique promises efficient measurement of subcellular motions with high sensitivity and low artifact involvement, suggesting high potential for in vivo and in situ applications.
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