Object‐Oriented Segmentation of Cell Nuclei in Fluorescence Microscopy Images
Sign Up to like & getrecommendations! Published in 2018 at "Cytometry Part A"
DOI: 10.1002/cyto.a.23594
Abstract: Cell nucleus segmentation remains an open and challenging problem especially to segment nuclei in cell clumps. Splitting a cell clump would be straightforward if the gradients of boundary pixels in‐between the nuclei were always higher… read more here.
Keywords: microscopy; segmentation; fluorescence microscopy; level ... See more keywords
Regularization Methods in the Analysis of a Series of Scintillation Fluorescence Microscopy Images
Sign Up to like & getrecommendations! Published in 2021 at "Computational Mathematics and Modeling"
DOI: 10.1007/s10598-021-09520-3
Abstract: We consider the construction of high-resolution images from a time series of fluorescence microscopy images obtained using a scintillator. A regularization method is applied and the results are compared for various stabilizers, including the RED… read more here.
Keywords: microscopy; regularization methods; fluorescence microscopy; microscopy images ... See more keywords
Myelin detection in fluorescence microscopy images using machine learning
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Neuroscience Methods"
DOI: 10.1016/j.jneumeth.2020.108946
Abstract: BACKGROUND The myelin sheath produced by glial cells insulates the axons, and supports the function of the nervous system. Myelin sheath degeneration causes neurodegenerative disorders, such as multiple sclerosis (MS). There are no therapies for… read more here.
Keywords: microscopy images; myelin detection; machine learning; microscopy ... See more keywords
Likelihood-based structural analysis of electron microscopy images.
Sign Up to like & getrecommendations! Published in 2018 at "Current opinion in structural biology"
DOI: 10.1016/j.sbi.2018.03.004
Abstract: Likelihood-based analysis of single-particle electron microscopy images has contributed much to the recent improvements in resolution. By treating particle orientations and classes probabilistically, uncertainties in the reconstruction process are explicitly accounted for, and the risk… read more here.
Keywords: likelihood based; microscopy; analysis; microscopy images ... See more keywords
Atom-by-atom chemical identification from scanning transmission electron microscopy images in presence of noise and residual aberrations.
Sign Up to like & getrecommendations! Published in 2021 at "Ultramicroscopy"
DOI: 10.1016/j.ultramic.2021.113292
Abstract: The simple dependence of the intensity in annular dark field scanning transmission electron microscopy images on the atomic number provides (to some extent) chemical information about the sample, and even allows an elemental identification in… read more here.
Keywords: microscopy; microscopy images; electron microscopy; identification ... See more keywords
In search of best automated model: Explaining nanoparticle TEM image segmentation.
Sign Up to like & getrecommendations! Published in 2021 at "Ultramicroscopy"
DOI: 10.1016/j.ultramic.2021.113437
Abstract: Over the years, computer scientists are working on building models that aid the scientific community in many ways by cutting laboratory expenses or by saving time. Such models find useful applications in microscopy images as… read more here.
Keywords: tem; microscopy; segmentation; model ... See more keywords
Investigation of podosome ring protein arrangement using localization microscopy images.
Sign Up to like & getrecommendations! Published in 2017 at "Methods"
DOI: 10.1016/j.ymeth.2016.11.005
Abstract: Podosomes are adhesive structures formed on the plasma membrane abutting the extracellular matrix of macrophages, osteoclasts, and dendritic cells. They consist of an f-actin core and a ring structure composed of integrins and integrin-associated proteins.… read more here.
Keywords: microscopy; podosome ring; using localization; microscopy images ... See more keywords
Segmenting Microscopy Images of Multi-Well Plates Based on Image Contrast
Sign Up to like & getrecommendations! Published in 2017 at "Microscopy and Microanalysis"
DOI: 10.1017/s1431927617012375
Abstract: Abstract Image segmentation is a key process in analyzing biological images. However, it is difficult to detect the differences between foreground and background when the image is unevenly illuminated. The unambiguous segmenting of multi-well plate… read more here.
Keywords: well plates; image; multi well; microscopy ... See more keywords
Chirality Analysis of Complex Microparticles using Deep Learning on Realistic Sets of Microscopy Images.
Sign Up to like & getrecommendations! Published in 2023 at "ACS nano"
DOI: 10.1021/acsnano.2c12056
Abstract: Nanoscale chirality is an actively growing research field spurred by the giant chiroptical activity, enantioselective biological activity, and asymmetric catalytic activity of chiral nanostructures. Compared to chiral molecules, the handedness of chiral nano- and microstructures… read more here.
Keywords: electron microscopy; microscopy; microscopy images; analysis ... See more keywords
A convolutional neural network segments yeast microscopy images with high accuracy
Sign Up to like & getrecommendations! Published in 2020 at "Nature Communications"
DOI: 10.1038/s41467-020-19557-4
Abstract: The identification of cell borders (‘segmentation’) in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exhibit irregular features. We… read more here.
Keywords: microscopy; convolutional neural; microscopy images; network segments ... See more keywords
Test-time augmentation for deep learning-based cell segmentation on microscopy images
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-61808-3
Abstract: Recent advancements in deep learning have revolutionized the way microscopy images of cells are processed. Deep learning network architectures have a large number of parameters, thus, in order to reach high accuracy, they require a… read more here.
Keywords: microscopy; segmentation; deep learning; microscopy images ... See more keywords