Cell nuclei detection using globally optimal active contours with shape prior

Cell nuclei detection in fluorescent microscopic images is an important and time consuming task for a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make this a challenging task for automated detection of individual nuclei using image analysis. This paper proposes a novel and robust detection method based on the active contour framework. The method exploits prior knowledge of the nucleus shape in order to better detect individual nuclei. The method is formulated as the optimization of a convex energy function. The proposed method shows accurate detection results even for clusters of nuclei where state of the art methods fail

An image analysis toolbox for high-throughput C. elegans assays

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available through the open-source CellProfiler project and enables objective scoring of whole-worm high-throughput image-based assays of C. elegans for the study of diverse biological pathways that are relevant to human disease.National Institutes of Health (U.S.) (U54 EB005149

Microscopy-BIDS: An extension to the brain imaging data structure for microscopy data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI

Label-free segmentation of co-cultured cells on a nanotopographical gradient

The function and fate of cells is influenced by many different factors, one of which is surface topography of the support culture substrate. Systematic studies of nanotopography and cell response have typically been limited to single cell types and a small set of topographical variations. Here, we show a radical expansion of experimental throughput using automated detection, measurement, and classification of co-cultured cells on a nanopillar array where feature height changes continuously from planar to 250 nm over 9 mm. Individual cells are identified and characterized by more than 200 descriptors, which are used to construct a set of rules for label-free segmentation into individual cell types. Using this approach we can achieve label-free segmentation with 84% confidence across large image data sets and suggest optimized surface parameters for nanostructuring of implant devices such as vascular stents

Label-free cell cycle analysis for high-throughput imaging flow cytometry

Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types

Proximity-dependent initiation of hybridization chain reaction

Sensitive detection of protein interactions and post-translational modifications of native proteins is a challenge for research and diagnostic purposes. A method for this, which could be used in point-of-care devices and high-throughput screening, should be reliable, cost effective and robust. To achieve this, here we design a method (proxHCR) that combines the need for proximal binding with hybridization chain reaction (HCR) for signal amplification. When two oligonucleotide hairpins conjugated to antibodies bind in close proximity, they can be activated to reveal an initiator sequence. This starts a chain reaction of hybridization events between a pair of fluorophore-labelled oligonucleotide hairpins, generating a fluorescent product. In conclusion, we show the applicability of the proxHCR method for the detection of protein interactions and posttranslational modifications in microscopy and flow cytometry. As no enzymes are needed, proxHCR may be an inexpensive and robust alternative to proximity ligation assays

Intradermal Indocyanine Green for In Vivo Fluorescence Laser Scanning Microscopy of Human Skin: A Pilot Study

BACKGROUND: In clinical diagnostics, as well as in routine dermatology, the increased need for non-invasive diagnosis is currently satisfied by reflectance laser scanning microscopy. However, this technique has some limitations as it relies solely on differences in the reflection properties of epidermal and dermal structures. To date, the superior method of fluorescence laser scanning microscopy is not generally applied in dermatology and predominantly restricted to fluorescein as fluorescent tracer, which has a number of limitations. Therefore, we searched for an alternative fluorophore matching a novel skin imaging device to advance this promising diagnostic approach. METHODOLOGY/PRINCIPAL FINDINGS: Using a Vivascope®-1500 Multilaser microscope, we found that the fluorophore Indocyanine-Green (ICG) is well suited as a fluorescent marker for skin imaging in vivo after intradermal injection. ICG is one of few fluorescent dyes approved for use in humans. Its fluorescence properties are compatible with the application of a near-infrared laser, which penetrates deeper into the tissue than the standard 488 nm laser for fluorescein. ICG-fluorescence turned out to be much more stable than fluorescein in vivo, persisting for more than 48 hours without significant photobleaching whereas fluorescein fades within 2 hours. The well-defined intercellular staining pattern of ICG allows automated cell-recognition algorithms, which we accomplished with the free software CellProfiler, providing the possibility of quantitative high-content imaging. Furthermore, we demonstrate the superiority of ICG-based fluorescence microscopy for selected skin pathologies, including dermal nevi, irritant contact dermatitis and necrotic skin. CONCLUSIONS/SIGNIFICANCE: Our results introduce a novel in vivo skin imaging technique using ICG, which delivers a stable intercellular fluorescence signal ideal for morphological assessment down to sub-cellular detail. The application of ICG in combination with the near infrared laser opens new ways for minimal-invasive diagnosis and monitoring of skin disorders