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We propose to reconstruct biological samples using calibration beads to perform numerical autofocusing in in-line holographic microscopy. The approach is based on a joint inversion using both a parametric and a regularized inversion method.

Research is continuously developing imaging methods to better understand the structure and function of biological systems. In this paper, we describe our work to develop lens-free microscopy as a novel mean to observe and quantify cells in 2D and 3D cell culture conditions. At first, we developed a lens-free video microscope based on multiple wavelength acquisitions to perform time-lapse 2D imaging of dense cell culture inside the incubator. We demonstrated that novel phase retrieval techniques enable imaging thin cell samples with high concentration (~15000 cells over a large field of view of 29.4 mm2). The experimental data can next be further analyzed with existing cell profiling and tracking algorithms. As an example, we showed that a 7 days acquisition of a culture of HeLa cells leads to a dataset featuring 2.106 cell point measurements and 104 cell cycle tracks. Recently, we extended our work to the video-microscopy of 3D organoids culture. We showed the capability of lens-free microscopy to perform 3D+time acquisitions of 3D organoids culture. To our knowledge, our technique is the only one able to reconstruct very large volumes of 3D cell culture (~5 mm3) by phase contrast imaging. This new mean of microscopy allowed us to observe a broad range of phenomena present in 3D environments, e.g. self-organizations, displacement of large clusters, merging and interconnection over long distances (>1 mm). In addition, this 3D microscope can capture the interactions of single cells and organoids with their 3D environment, e.g. traction forces generated by large cell aggregates over long distances, up to 1.5 mm. Overall, lens-free microscopy techniques favor ease of use and label-free experimentations as well as time-lapse acquisitions of large datasets. Importantly, we consider that these lens-free microscopy technique can thus expand the repertoire of phenomena that can be studied within 2D and 3D organoids cultures.

We developed 2D and 3D lens-free microscopes, based on the data processing of raw diffraction images. By nature, these systems allows imaging large field of view of unlabeled samples and easily provide time-lapses.

Editors: Thomas G. Brown, Carol J. Cogswell, Tony Wilson; We propose a three-dimensional (3D) imaging platform based on lens-free microscopy to perform multi-angle acquisitions on 3D cell cultures embedded in extracellular matrix (ECM). We developed algorithms based on the Fourier diffraction theorem to perform fully 3D reconstructions of biological samples and we adapted the lens-free microscope to incubator conditions. Here we demonstrate for the first time, 3D+time lens-free acquisitions of 3D cell culture over 8 days directly into the incubator. The 3D reconstructed volume is as large as ~5 mm3 and provides a unique way to observe in the same 3D cell culture experiment multiple cell migration strategies. Namely, in a 3D cell culture of prostate epithelial cells embedded within a Matrigel® matrix, we are able to distinguish single cell ’leaders’, migration of cell clusters, migration of large aggregates of cells, and also close-gap and large-scale branching. In addition, we observe long-scale 3D deformations of the ECM that modify the geometry of the 3D cell culture. Interestingly, we also observed the opposite, i.e. we found that large aggregates of cells may deform the ECM by generating traction forces over very long distances. In sum we put forward a novel 3D lens-free microscopy tomographic technique to study the single and collective cell migrations, the cell-to-cell interactions and the cell-to-matrix interactions.

In-line digital holography is a simple yet powerful tool to image absorbing and/or phase objects. Nevertheless, the loss of the phase of the complex wavefront on the sensor can be critical in the reconstruction process. The simplicity of the setup must thus be counterbalanced by dedicated reconstruction algorithms, such as inverse approaches, in order to retrieve the object from its hologram. In the case of simple objects for which the diffraction pattern produced in the hologram plane can be modeled using few parameters, a model fitting algorithm is very effective. However, such an approach fails to reconstruct objects with more complex shapes, and an image reconstruction technique is then needed. The improved flexibility of these methods comes at the cost of a possible loss of reconstruction accuracy. In this work, we combine the two approaches (model fitting and regularized reconstruction) to benefit from their respective advantages. The sample to be reconstructed is modeled as the sum of simple parameterized objects and a complex-valued pixelated transmittance plane. These two components jointly scatter the incident illumination, and the resulting interferences contribute to the intensity on the sensor. The proposed hologram reconstruction algorithm is based on alternating a model fitting step and a regularized inversion step. We apply this algorithm in the context of fluid mechanics, where holograms of evaporating droplets are analyzed. In these holograms, the high contrast fringes produced by each droplet tend to mask the diffraction pattern produced by the surrounding vapor wake. With our method, the droplet and the vapor wake can be jointly reconstructed.

Lensfree imaging is an emerging microscopy technique based on in-line holography as invented by Gabor in 1948. Albeit the existence of the method since decades, the recent development of digital sensors, helped the realization of its full potential. Over the recent years, innovations and improvements in CMOS imaging technology design and fabrication have allowed to decrease the pixel pitch down to ∼1μm and the number of pixels has dramatically increased up to 250 million of pixels. As a result, the performance of lensfree microscopy, which features a bare CMOS sensor without any magnification optics, have tremendously increased while keeping the design simple, robust, and at a reasonable low cost. The detection ability improved from 10 μm (cell) in 2009, to 1 μm (bacteria) in 2010, down to 100 nm beads in 2012, paving the way to the detection of viruses in 2013.