Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups. It also briefly discusses the present and future perspectives of 2D and 3D QPI research based on digital holographic microscopy, holographic tomography, and their applications.

Quantification of basic cell functions is a preliminary step to understand complex cellular mechanisms, for e.g., to test compatibility of biomaterials, to assess the effectiveness of drugs and siRNAs, and to control cell behavior. However, commonly used quantification methods are label-dependent, and end-point assays. As an alternative, using our lensfree video microscopy platform to perform high-throughput real-time monitoring of cell culture, we introduce specifically devised metrics that are capable of non-invasive quantification of cell functions such as cell-substrate adhesion, cell spreading, cell division, cell division orientation and cell death. Unlike existing methods, our platform and associated metrics embrace entire population of thousands of cells whilst monitoring the fate of every single cell within the population. This results in a high content description of cell functions that typically contains 25,000 – 900,000 measurements per experiment depending on cell density and period of observation. As proof of concept, we monitored cell-substrate adhesion and spreading kinetics of human Mesenchymal Stem Cells (hMSCs) and primary human fibroblasts, we determined the cell division orientation of hMSCs, and we observed the effect of transfection of siCellDeath (siRNA known to induce cell death) on hMSCs and human Osteo Sarcoma (U2OS) Cells.

Lensless on-chip imaging is a promising technique to count and monitor cells and micro-objects in liquid sample. In this paper we apply this technique to the observation of µL sample containing bacteria evaporated onto a microscope slide. Compared with previously reported techniques, a large improvement in signal to noise ratio is obtained due to the presence of a few μm thick wetting film creating a micro-lens on top of each bacteria. In these conditions, standard CMOS sensor are able to detect micro-objects as small as few μm, e.g. E.coli and Bacillus subtilis bacteria and 1 μm polymer beads with a large signal to noise ratio of 45 ± 10. An overall detection efficiency of 85 ± 7% and a co-localization error of σ_1D = 1.1μm compared with reference fluorescence microscopy images are achieved. This novel technique will be used as a pre-positioning tool prior to other optical identification methods, e.g. Raman spectroscopy.

Lens-free microscopy multispectral acquisitions are processed with an inverse problem approach: a multispectral total variation criterion is defined and minimized with the conjugate gradients method. Reconstruction results show that the method is efficient to recover the phase image of densely packed cells.

We propose a three-dimensional (3D) imaging platform based on lens-free microscopy to perform multiangle acquisitions on 3D cell cultures embedded in extracellular matrices. Lens-free microscopy acquisitions present some inherent issues such as the lack of phase information on the sensor plane and a limited angular coverage. We developed and compared three different algorithms based on the Fourier diffraction theorem to obtain fully 3D reconstructions. These algorithms present an increasing complexity associated with a better reconstruction quality. Two of them are based on a regularized inverse problem approach. To compare the reconstruction methods in terms of artefact reduction, signal-to-noise ratio, and computation time, we tested them on two experimental datasets: an endothelial cell culture and a prostate cell culture grown in a 3D extracellular matrix with large reconstructed volumes up to $\sim 5{\mathrm{mm}}^3$ with a resolution sufficient to resolve isolated single cells. The lens-free reconstructions compare well with standard microscopy.