In this paper we investigate the use of a digital holographic microscope, with partial spatial coherent illumination, for the automated detection and tracking of spermatozoa. This in vitro technique for the analysis of quantitative parameters is useful for assessment of semen quality. In fact, thanks to the capabilities of digital holography, the developed algorithm allows us to resolve in-focus amplitude and phase maps of the cells under study, independently of focal plane of the sample image. We have characterized cell motility on clinical samples of seminal fluid. In particular, anomalous sperm cells were characterized and the quantitative motility parameters were compared to those of normal sperm.

In this paper, we investigate the use of a digital holographic microscope working with partially coherent spatial illumination for an automated detection and classification of living organisms. A robust automatic method based on the computation of propagating matrices is proposed to detect the 3D position of organisms. We apply this procedure to the evaluation of drinking water resources by developing a classification process to identify parasitic protozoan Giardia lamblia cysts among two other similar organisms. By selecting textural features from the quantitative optical phase instead of morphological ones, a robust classifier is built to propose a new method for the unambiguous detection of Giardia lamblia cyst that present a critical contamination risk.

Traditional taxonomic identification of planktonic organisms is based on light microscopy, which is both time‐ consuming and tedious. In response, novel ways of automated (machine) identification, such as flow cytometry, have been investigated over the last two decades. To improve the taxonomic resolution of particle analysis, recent developments have focused on “imaging‐ in‐ flow,” i.e., the ability to acquire microscopic images of planktonic cells in a flow‐ through mode. Imaging‐ in‐ flow systems are traditionally based on classical brightfield microscopy and are faced with a number of issues that decrease the classification performance and accuracy (e.g., projection variance of cells, migration of cells out of the focus plane). Here, we demonstrate that a combination of digital holographic microscopy (DHM) with imaging‐ in‐ flow can improve the detection and classification of planktonic organisms. In addition to light intensity information, DHM provides quantitative phase information, which generates an additional and independent set of features that can be used in classification algorithms. Moreover, the capability of digitally refocusing greatly increases the depth of field, enables a more accurate focusing of cells, and reduces the effects of position variance. Nanoplanktonic organisms similar in shape were successfully classified from images captured with an off‐ axis DHM with partial coherence. Textural features based on DHM phase information proved more efficient in separating the three tested phytoplankton species compared with shape‐ based features or textural features based on light intensity. An overall classification score of 92.4% demonstrates the potential of holographic‐ based imaging‐ in‐ flow for similar looking organisms in the nanoplankton range.

We analyze the dependency and the accuracy of the refocusing criterion based on the integrated modulus amplitude in the case of amplitude object. Analytical dependencies on the defocus distance and the numerical aperture are found. This theoretical prediction for the refocusing criterion is well supported by simulation. We study also the robustness of the refocusing criterion by adding salt and pepper and speckle-type noises. We demonstrate that the refocusing criterion is robust up to an significant level of noise that can perturb the holograms.

Improving image quality in digital holographic microscopy is achievable by using partial spatial coherence (PSC) illumination instead of fully coherent illumination. This Letter presents simple theoretical models to quantitatively assess the reduction of noise as a function of both the spatial coherence of the illumination and the defocus distance of the noise source. The first developed model states that the effect of the PSC can be studied by discretizing the field of view in the plane of the noise source. The second model, following a continuous approach, corroborates the discrete model and extends it. Experimental results confirm theoretical expectations.