Quantitative phase imaging of biological cells using lensless inline holographic microscopy through sparsity-assisted iterative phase retrieval algorithm

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 ∼29mm2. 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.