Background intensity correction for terabyte-sized time-lapse images

Single Image-Based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy

High-resolution functional 2-photon microscopy of neural activity is a cornerstone technique in current neuroscience, enabling, for instance, the image-based analysis of relations of the organization of local neuron populations and their temporal neural activity patterns. Interpreting local image intensity as a direct quantitative measure of neural activity presumes, however, a consistent within- and across-image relationship between the image intensity and neural activity, which may be subject to interference by illumination artifacts. In particular, the so-called vignetting artifact—the decrease of image intensity toward the edges of an image—is, at the moment, widely neglected in the context of functional microscopy analyses of neural activity, but potentially introduces a substantial center-periphery bias of derived functional measures. In the present report, we propose a straightforward protocol for single image-based vignetting correction. Using immediate-early gene-based 2-photon microscopic neural image data of the mouse brain, we show the necessity of correcting both image brightness and contrast to improve within- and across-image intensity consistency and demonstrate the plausibility of the resulting functional data.

Open Source 3D-printed focussing mechanism for cellphone-based cellular microscopy

The need to improve access to microscopes in low-resource and educational settings coupled with the global proliferation of camera-enabled cellphones has recently led to an explosion in new developments in portable, low-cost microscopy. The availability of accurate ball lenses has resulted in many variants of van Leeuwenhoek-like microscopes. Combined with cellphones, they have the potential for use as portable microscopes in education and clinics. The need for reproducibility in such applications implies that control over focus is critical. Here, we describe a 3D-printed focussing mechanism based on a rack and pinion mechanism, coupled to a ball lens- based microscope. We quantify the time-stability of the focussing mechanism through an edge-based contrast measure used in autofocus cameras and apply it to 'thin smear' blood sample infected with Plasmodium as well as onion skin cells. We show that stability of the z-focus is in the micrometre range. This development could, we believe, serve to further enhance the utility of a low-cost and robust microscope and encourage further developments in field microscopes based on the Open Source principle. LAY DESCRIPTION: The wide spread of cellphones with cameras makes them an attractive platform for digital microscopy. Such microscopes could help improve microscope access in clinics and classrooms in the form of 'field microscopes', if they could be adapted for imaging cells. We integrate a 3D printed focussing mechanism made with recyclable plastic with ball-lens microscope of the Leeuwenhoek type. We demonstrate how the device can help stabilise to a focal plane for acquiring movies of a thin-smear of blood infected with Plasmodium and onion skin cells using a cellphone. The stability of focus is expectedly less precise as compared to research-grade microscopes, but is of the range of a few micrometers. We believe, the focussing device demonstrates it is possible to obtain reliable and reproducible images of typical samples used in clinics and classrooms. By making the design files of this device open-source we believe it could serve as a small step in improved, affordable and accurate 'field microscopes'.

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses

Image mosaicing permits achieving one high-resolution image, extending the visible area of the sample while keeping the same resolution. However, intensity inhomogeneity of the stitched images can alter measurements and the right perception of the original sample. The problem can be solved by flat-field correcting the images through the vignetting function. Vignetting correction has been widely addressed for grey-level images, but not for colour ones. In this work, a practical solution for the colour vignetting correction in microscopy, also facing the problem of saturated pixels, is described. In order to assess the quality of the proposed approach, five different tonal correction approaches were quantitatively compared using state-of-the-art metrics and seven pairs of partially overlapping images of seven different samples. The results obtained proved that the proposed approach allows obtaining high quality colour flat-field corrected images and seamless mosaics without employing any blending adjustment. In order to give the opportunity to easily obtain seamless mosaics ready for quantitative analysis, the described vignetting correction method has been implemented in an upgraded release of MicroMos (version 3.0), an open-source software specifically designed to automatically obtain mosaics of partially overlapped images.

Large-scale time-lapse microscopy of Oct4 expression in human embryonic stem cell colonies

Identification and quantification of the characteristics of stem cell preparations is critical for understanding stem cell biology and for the development and manufacturing of stem cell based therapies. We have developed image analysis and visualization software that allows effective use of time-lapse microscopy to provide spatial and dynamic information from large numbers of human embryonic stem cell colonies. To achieve statistically relevant sampling, we examined >680 colonies from 3 different preparations of cells over 5 days each, generating a total experimental dataset of 0.9 terabyte (TB). The 0.5 Giga-pixel images at each time point were represented by multi-resolution pyramids and visualized using the Deep Zoom Javascript library extended to support viewing Giga-pixel images over time and extracting data on individual colonies. We present a methodology that enables quantification of variations in nominally-identical preparations and between colonies, correlation of colony characteristics with Oct4 expression, and identification of rare events.

Survey statistics of automated segmentations applied to optical imaging of mammalian cells

BACKGROUND

The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements.

METHODS

We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories.

RESULTS

The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue.

CONCLUSIONS

The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.