Extended depth of focus in optical microscopy: Assessment of existing methods and a new proposal

Assessing the impact of spatial coherence on the sinusoidal linear Fresnel zone plate's depth of focus

This research examines, using both theory and experimentation, how a light beam's spatial coherence affects a sinusoidal linear Fresnel zone plate's depth of focus. We generate a one-dimensional partially coherent Gaussian Schell-model beam from a coherent laser beam through putting a rotating diffuser near to the common focal plane of two cylindrical lenses in a 2f-system. By adjusting the beam spot size on the diffuser, one may modify the coherence width of the produced beam. Our findings demonstrate that when the coherence width of the partly coherent beam drops, the zone plate's depth of focus increases. Not only is it claimed that the experimental results validate the theoretical conclusions, but a mathematical link is also established between the experimental parameter used to manipulate the light coherence and the theoretically obtained coherence width. This topic has many applications in the field of optical, microscopy, optical trapping, imaging systems and biomedical.

DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus

Depth of focus (DOF) is defined as the axial range in which the specimen stage moves without losing focus while the imaging apparatus remains stable. It may not be possible to capture an image that includes the entire specimen in focus due to the narrow DOF in microscopic systems. Extended depth of focus (EDOF) is used to overcome this limitation in microscopic systems. Although the researchers have developed so many EDOF microscope approaches, this research field still has some crucial shortcomings such as high computational costs, complexity and execution time, requiring additional equipment, low precise characterization of curves, and edges in images, varying performance depending on the specimen and microscope, using only gray levels of input images to acquire the pixel's focus values. In order to minimize these shortcomings and comprehensively analyze the performance of EDOF approaches, a novel multi-focus image data set is generated, and a deep learning-based EDOF microscope approach is proposed in this study. When compared with the state-of-art EDOF approaches, our study provides various crucial contributions such as the first EDOF approach based on unsupervised deep learning, providing more accurate and specimen-free EDOF, generating a novel multi-focus image data, not requiring any pre- or post-processing technique and acquiring the pixel's focus degrees using deep features. In order to evaluate the effectiveness of the suggested approach, 20 different EDOF approaches are applied to a multi-focus image data set containing 9 image collections (4 synthetic and 5 microscope image collections) in total. Performance analysis metrics with and without requiring a reference image are preferred to identify which EDOF microscope approach can extract more essential details from the multi-focus images for the synthetic and microscope image collections, which are Root Mean Square Error (RMSE), Peak Signal Noise Ratio (PSNR), Universal Quality Index (UQI), Correlation Coefficient (CC), Perception-based Image Quality Evaluator (PIQE), Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE), Extension of Universal Quality Index for N Images (UQIN), and Naturalness Image Quality Evaluator (NIQE). Objective and subjective analysis of this study demonstrates that unsupervised deep learning model is more efficient to transmit crucial details from multi-focus images. Moreover, the suggested EDOF microscope approach with highest PSNR, UQI, CC, UQIN and lowest RMSE, PIQE, BRISQUE, NIQE produces higher performance than the state-of-art approaches.

Slide Over: Advances in Slide-Free Optical Microscopy as Drivers of Diagnostic Pathology

Conventional analysis using clinical histopathology is based on bright-field microscopy of thinly sliced tissue specimens. Although bright-field microscopy is a simple and robust method of examining microscope slides, the preparation of the slides needed is a lengthy and labor-intensive process. Slide-free histopathology, however, uses direct imaging of intact, minimally processed tissue samples using advanced optical-imaging systems, bypassing the extended workflow now required for the preparation of tissue sections. This article explains the technical basis of slide-free microscopy, reviews common slide-free optical microscopy techniques, and discusses the opportunities and challenges involved in clinical implementation.

Digital refocusing and extended depth of field reconstruction in Fourier ptychographic microscopy

Fourier ptychography microscopy (FPM) is a recently developed microscopic imaging method that allows the recovery of a high-resolution complex image by combining a sequence of bright and darkfield images acquired under inclined illumination. The capacity of FPM for high resolution imaging at low magnification makes it particularly attractive for applications in digital pathology which require imaging of large specimens such as tissue sections and blood films. To date most applications of FPM have been limited to imaging thin samples, simplifying both image reconstruction and analysis. In this work we show that, for samples of intermediate thickness (defined here as less than the depth of field of a raw captured image), numerical propagation of the reconstructed complex field allows effective digital refocusing of FPM images. The results are validated by comparison against images obtained with an equivalent high numerical aperture objective lens. We find that post reconstruction refocusing (PRR) yields images comparable in quality to adding a defocus term to the pupil function within the reconstruction algorithm, while reducing computing time by several orders of magnitude. We apply PRR to visualize FPM images of Giemsa-stained peripheral blood films and present a novel image processing pipeline to construct an effective extended depth of field image which optimally displays the 3D sample structure in a 2D image. We also show how digital refocusing allows effective correction of the chromatic focus shifts inherent to the low magnification objective lenses used in FPM setups, improving the overall quality of color FPM images.

Relaxation of the Crowther criterion in multislice tomography

For objects larger than the depth of focus of an imaging system, one must account for wavefield propagation effects within the object as is done in diffraction tomography, diffraction microscopy, and multislice ptychographic tomography. We show here that if the imaging method used reconstructs Na planes along each viewing direction, one can reduce the number of illumination directions required to fill Fourier space by a factor of 1/Na, relaxing the usual Crowther criterion for tomography. This provides a conceptual basis to explain two recent experiments where multiple axial planes were imaged per viewing direction, and tomographic images were obtained with good 3D spatial resolution, even though fewer illumination directions were used than one would have expected from the Crowther criterion.

A new holistic 3D non-invasive analysis of cellular distribution and motility on fibroin-alginate microcarriers using light sheet fluorescent microscopy

Cell interaction with biomaterials is one of the keystones to developing medical devices for tissue engineering applications. Biomaterials are the scaffolds that give three-dimensional support to the cells, and are vectors that deliver the cells to the injured tissue requiring repair. Features of biomaterials can influence the behaviour of the cells and consequently the efficacy of the tissue-engineered product. The adhesion, distribution and motility of the seeded cells onto the scaffold represent key aspects, and must be evaluated in vitro during the product development, especially when the efficacy of a specific tissue-engineered product depends on viable and functional cell loading. In this work, we propose a non-invasive and non-destructive imaging analysis for investigating motility, viability and distribution of Mesenchymal Stem Cells (MSCs) on silk fibroin-based alginate microcarriers, to test the adhesion capacity of the fibroin coating onto alginate which is known to be unsuitable for cell adhesion. However, in depth characterization of the biomaterial is beyond the scope of this paper. Scaffold-loaded MSCs were stained with Calcein-AM and Ethidium homodimer-1 to detect live and dead cells, respectively, and counterstained with Hoechst to label cell nuclei. Time-lapse Light Sheet Fluorescent Microscopy (LSFM) was then used to produce three-dimensional images of the entire cells-loaded fibroin/alginate microcarriers. In order to quantitatively track the cell motility over time, we also developed an open source user friendly software tool called Fluorescent Cell Tracker in Three-Dimensions (F-Tracker3D). Combining LSFM with F-Tracker3D we were able for the first time to assess the distribution and motility of stem cells in a non-invasive, non-destructive, quantitative, and three-dimensional analysis of the entire surface of the cell-loaded scaffold. We therefore propose this imaging technique as an innovative holistic tool for monitoring cell-biomaterial interactions, and as a tool for the design, fabrication and functionalization of a scaffold as a medical device.

Cell Counting and Viability Assessment of 2D and 3D Cell Cultures: Expected Reliability of the Trypan Blue Assay

BACKGROUND

Whatever the target of an experiment in cell biology, cell counting and viability assessment are always computed. The Trypan Blue (TB) assay was proposed about a century ago and is still the most widely used method to perform cell viability analysis. Furthermore, the combined use of TB with a haemocytometer is also considered the standard approach to estimate cell population density. There are numerous research articles reporting the use of TB assays to compute cell number and viability of 2D and 3D cultures. However, the literature still lacks studies regarding the reliability of the TB assay in terms of assessment of its repeatability and reproducibility.

METHODS

We compared the TB assay's measurements obtained by two biologists who analysed 105 different samples in double-blind for a total of 210 counts performed. We measured: (a) the repeatability of the count performed by the same operator; (b) the reproducibility of counts performed by the two operators.

RESULTS

There were no significant differences in the results obtained with 2D and 3D cell cultures: we estimated an approximate variability of 5% when the TB assay was used to assess the viability of the culture, and a variability of around 20% when it was used to determine the cell population density.

CONCLUSIONS

The main aim of this study was to make researchers aware of potential measurement errors when TB is used with a haemocytometer for counting and viability measurements in 2D and 3D cultures. We believe that these results can help researchers to determine whether the expected reliability of the TB assay is compliant with their applications.

Single-image based methods used for non-invasive volume estimation of cancer spheroids: a practical assessing approach based on entry-level equipment

BACKGROUND

Cancer multicellular spheroids are commonly used as 3D tumour models for testing drugs and radiotherapy treatments. The volume plays a key role in analysis of the results. Several methods have been proposed in the literature to compute the spheroid's volume from one 2D microscopy image (i.e. a single projection). However, the literature lacks reviews summarising the different methods available. Furthermore, there are no well-established approaches by which to compare the different methods and determine the best one.

OBJECTIVE

In this work we (a) revise the existing single-image based methods used to estimate the volume of multicellular spheroids, also providing different implementations for classical spherical and ellipsoidal pre-defined models; (b) present an upgrade of a volume estimation software recently proposed, Reconstruction and Visualization from a Single Projection (ReViSP), just validated by using four real spheroids imaged in 3D with a light-sheet microscope; (c) propose a quality assessing approach for single-image based methods, relying on 3D home-made macroscopic synthetic models mimicking the shapes of real multicellular spheroids.

RESULTS

Seven image-based methods used to estimate the volume of spheroids were compared using six 3D home-made synthetic models. First, the material used to make the synthetic models was characterised to estimate its density. Then, the ground-truth volume of the 3D models was measured by simply weighing them. The volume instances estimated by the different methods were compared with ground truth. ReViSP attained the best result three times out of six and on average.

CONCLUSIONS

The results obtained proved that (a) different implementations for the classical spherical and ellipsoidal pre-defined models may lead to very different results; (b) ReViSP is the best single-image based method available today to estimate the volume of multicellular spheroids.

AnaSP: a software suite for automatic image analysis of multicellular spheroids

Today, more and more biological laboratories use 3D cell cultures and tissues grown in vitro as a 3D model of in vivo tumours and metastases. In the last decades, it has been extensively established that multicellular spheroids represent an efficient model to validate effects of drugs and treatments for human care applications. However, a lack of methods for quantitative analysis limits the usage of spheroids as models for routine experiments. Several methods have been proposed in literature to perform high throughput experiments employing spheroids by automatically computing different morphological parameters, such as diameter, volume and sphericity. Nevertheless, these systems are typically grounded on expensive automated technologies, that make the suggested solutions affordable only for a limited subset of laboratories, frequently performing high content screening analysis. In this work we propose AnaSP, an open source software suitable for automatically estimating several morphological parameters of spheroids, by simply analyzing brightfield images acquired with a standard widefield microscope, also not endowed with a motorized stage. The experiments performed proved sensitivity and precision of the segmentation method proposed, and excellent reliability of AnaSP to compute several morphological parameters of spheroids imaged in different conditions. AnaSP is distributed as an open source software tool. Its modular architecture and graphical user interface make it attractive also for researchers who do not work in areas of computer vision and suitable for both high content screenings and occasional spheroid-based experiments.

Cancer multicellular spheroids: volume assessment from a single 2D projection

Volume is one of the most important features for the characterization of a tumour on a macroscopic scale. It is often used to assess the effectiveness of care treatments, thus making its correct evaluation a crucial issue for patient care. Similarly, volume is a key feature on a microscopic scale. Multicellular cancer spheroids are 3D tumour models widely employed in pre-clinical studies to test the effects of drugs and radiotherapy treatments. Very few methods have been proposed to estimate the tumour volume arising from a 2D projection of multicellular spheroids, and even fewer have been designed to provide a 3D reconstruction of the tumour shape. In this work, we propose Reconstruction and Visualization from a Single Projection (ReViSP), an automatic method conceived to reconstruct the 3D surface and estimate the volume of single cancer multicellular spheroids, or even of spheroid cultures. As the input parameter ReViSP requires only one 2D projection, which could be a widefield microscope image. We assessed the effectiveness of our method by comparing it with other approaches. To this purpose, we used a new strategy that allowed us to achieve accurate volume measurements based on the analysis of home-made 3D objects, built by mimicking the spheroid morphology. The results confirmed the effectiveness of our method for both 3D reconstruction and volume assessment. ReViSP software is distributed as an open source tool.

Improving reliability of live/dead cell counting through automated image mosaicing

Cell counting is one of the basic needs of most biological experiments. Numerous methods and systems have been studied to improve the reliability of counting. However, at present, manual cell counting performed with a hemocytometer still represents the gold standard, despite several problems limiting reproducibility and repeatability of the counts and, at the end, jeopardizing their reliability in general. We present our own approach based on image processing techniques to improve counting reliability. It works in two stages: first building a high-resolution image of the hemocytometer's grid, then counting the live and dead cells by tagging the image with flags of different colours. In particular, we introduce GridMos (http://sourceforge.net/p/gridmos), a fully-automated mosaicing method to obtain a mosaic representing the whole hemocytometer's grid. In addition to offering more significant statistics, the mosaic "freezes" the culture status, thus permitting analysis by more than one operator. Finally, the mosaic achieved can thus be tagged by using an image editor, thus markedly improving counting reliability. The experiments performed confirm the improvements brought about by the proposed counting approach in terms of both reproducibility and repeatability, also suggesting the use of a mosaic of an entire hemocytometer's grid, then labelled trough an image editor, as the best likely candidate for the new gold standard method in cell counting.

Semi-quantitative monitoring of confluence of adherent mesenchymal stromal cells on calcium-phosphate granules by using widefield microscopy images

The analysis of cell confluence and proliferation is essential to design biomaterials and scaffolds to use as bone substitutes in clinical applications. Accordingly, several approaches have been proposed in the literature to estimate the area of the scaffold covered by cells. Nevertheless, most of the approaches rely on sophisticated equipment not employed for routine analyses, while the rest of them usually do not provide significant statistics about the cell distribution. This research aims at studying confluence and proliferation of mesenchymal stromal cells (MSC) adherent on OSPROLIFE(®), a commercial biomaterial in the form of granules. In particular, we propose a Computer Vision approach that can routinely be employed to monitor the surface of the single granules covered by cells because only a standard widefield fluorescent microscope is required. In order to acquire significant statistics data, we analyse wide-area images built by using MicroMos v2.0, an updated version of a previously published software specific for stitching brightfield and phase-contrast images manually acquired via a widefield microscope. In particular, MicroMos v2.0 permits to build accurate "mosaics" of fluorescent images, after correcting vignetting and photo-bleaching effects, providing a consistent representation of a sample region containing numerous granules. Then, our method allows to make automatically a statistically significant estimate of the percentage of the area of the single granules covered by cells. Finally, by analysing hundreds of granules at different time intervals we also obtained reliable data regarding cell proliferation, confirming that not only MSC adhere onto the OSPROLIFE(®) granules, but even proliferate over time.

Automated image mosaics by non-automated light microscopes: the MicroMos software tool

Light widefield microscopes and digital imaging are the basis for most of the analyses performed in every biological laboratory. In particular, the microscope's user is typically interested in acquiring high-detailed images for analysing observed cells and tissues, meanwhile being representative of a wide area to have reliable statistics. The microscopist has to choose between higher magnification factor and extension of the observed area, due to the finite size of the camera's field of view. To overcome the need of arrangement, mosaicing techniques have been developed in the past decades for increasing the camera's field of view by stitching together more images. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Or alternatively, the methods are conceived just to provide visually pleasant mosaics not suitable for quantitative analyses. This work presents a tool for building mosaics of images acquired with nonautomated light microscopes. The method proposed is based on visual information only and the mosaics are built by incrementally stitching couples of images, making the approach available also for online applications. Seams in the stitching regions as well as tonal inhomogeneities are corrected by compensating the vignetting effect. In the experiments performed, we tested different registration approaches, confirming that the translation model is not always the best, despite the fact that the motion of the sample holder of the microscope is apparently translational and typically considered as such. The method's implementation is freely distributed as an open source tool called MicroMos. Its usability makes building mosaics of microscope images at subpixel accuracy easier. Furthermore, optional parameters for building mosaics according to different strategies make MicroMos an easy and reliable tool to compare different registration approaches, warping models and tonal corrections.

Semi-automated 3D leaf reconstruction and analysis of trichome patterning from light microscopic images

Trichomes are leaf hairs that are formed by single cells on the leaf surface. They are known to be involved in pathogen resistance. Their patterning is considered to emerge from a field of initially equivalent cells through the action of a gene regulatory network involving trichome fate promoting and inhibiting factors. For a quantitative analysis of single and double mutants or the phenotypic variation of patterns in different ecotypes, it is imperative to statistically evaluate the pattern reliably on a large number of leaves. Here we present a method that enables the analysis of trichome patterns at early developmental leaf stages and the automatic analysis of various spatial parameters. We focus on the most challenging young leaf stages that require the analysis in three dimensions, as the leaves are typically not flat. Our software TrichEratops reconstructs 3D surface models from 2D stacks of conventional light-microscope pictures. It allows the GUI-based annotation of different stages of trichome development, which can be analyzed with respect to their spatial distribution to capture trichome patterning events. We show that 3D modeling removes biases of simpler 2D models and that novel trichome patterning features increase the sensitivity for inter-accession comparisons.

The patterning of trichomes (leaf hair) on the surface of a leaf is a paradigm for studying gene regulation in developmental processes. The statistical analysis of trichome patterning requires automated methods for the location of trichomes on a curved leaf surface. This is particularly challenging for young, strongly bent leaves. We have developed the TrichEratops software that reconstructs 3D leaf surfaces from 2D stacks of conventional light-microscopy pictures. TrichEratops also calculates statistical patterning features, thereby greatly facilitating the whole data acquisition process. We show, using two Arabidopsis thaliana mutants, that 3D modeling removes biases and increases the discriminatory power of trichome pattern analysis.