The twin image-free phase reconstruction is still a challenge with single-shot inline holographic systems. Existing solutions mostly are based on the inverse problem approaches or alternating projections. However, there exists a trade-off between phase retrieval and twin image elimination. Recent studies have introduced a hybrid method involving both the approaches to mitigate this trade-off. Following these works, we propose a single-shot sparsity-assisted iterative phase retrieval approach that applies a sparsity constraint in the object domain and formulates phase retrieval as a minimization problem. We demonstrate lensless digital inline holographic microscopy for imaging transparent and weakly scattering biological samples over a large field-of-view of . The proposed method achieves high fidelity phase reconstruction with faster convergence compared to the existing single-shot phase retrieval methods. We further demonstrate the phase quantification of label-free biological samples, such as cervical cells and RBCs, to highlight the potential of our technique in clinical applications.
Quantitative phase imaging of biological cells using lensless inline holographic microscopy through sparsity-assisted iterative phase retrieval algorithm
Ashwini S. Galande, Hanu Phani Ram Gurram, Aruna Priya Kamireddy, Vijaya Sree Venkatapuram, Qurratulain Hasan, Renu John; Quantitative phase imaging of biological cells using lensless inline holographic microscopy through sparsity-assisted iterative phase retrieval algorithm. J. Appl. Phys. 28 December 2022; 132 (24): 243102. https://doi.org/10.1063/5.0123677
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