For instance, the counting of protein structures, such as the ProMyelocytic Leukemia Nuclear Bodies (PML NB) found involved in chromatin remodeling, telomere biology, senescence or viral infections ( Lallemand-Breitenbach and de The, 2018), is achievable by applying a “2D counting” image analysis tool to first identify cells and then determine the number of contained PML NB ( Supplementary Figure S1A). However, researchers operating microscopes have to deal with a number of experimental challenges often requiring different types of image analysis procedures. Microscopy and image analysis significantly contribute to the advancement of research in life sciences. This plugin aims to provide interactive and zero-scripting customizable workflows for cell segmentation, vesicles counting, parent-child relation between objects, signal quantification, and results presentation all included in the same open-source napari viewer, and “few clicks away”. Here we present ZELDA, a new napari plugin that easily integrates the cutting-edge solutions offered by python ecosystem, such as scikit-image for image segmentation, matplotlib for data visualization, and napari multi-dimensional image viewer for 3D rendering. While several commercial packages are available on the market, fewer are the open-source solutions able to execute a complete 3D analysis workflow. Despite the availability of numerous algorithms for the 2D and 3D segmentation, the latter still offers some challenges for the end-users, who often do not have either an extensive knowledge of the existing software or coding skills to link the output of multiple tools. Furthermore, it is increasingly appreciated that to overcome the limitations of the 2D-view-based image analysis approaches and to correctly understand and interpret biological processes, a 3D segmentation of microscopy data sets becomes imperative. 2Department of Biology and Biochemistry, University of Bath, Bath, United Kingdomīioimage analysis workflows allow the measurement of sample properties such as fluorescence intensity and polarization, cell number, and vesicles distribution, but often require the integration of multiple software tools.1Crick Advanced Light Microscopy STP, The Francis Crick Institute, London, United Kingdom.doi: 10.Rocco D’Antuono 1* and Giuseppina Pisignano 2 Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. Kamentsky L, Jones TR, Fraser A, Bray M-A, Logan DJ, Madden KL, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. doi: 10.1016/j.jbiotec.2017.07.028Ĭarpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. KNIME for reproducible cross-domain analysis of life science data. ImageJ2: ImageJ for the next generation of scientific image data. Rueden CT, Schindelin J, Hiner MC, DeZonia BE, Walter AE, Arena ET, et al. 3D, three-dimensional FISH, fluorescent in situ hybridization GAPDH, glyceraldehyde 3-phosphate dehydrogenase WGA, wheat germ agglutinin.Įliceiri KW, Berthold MR, Goldberg IG, Ibáñez L, Manjunath BS, Martone ME, et al. Images were provided by Javier Frias Aldeguer and Nicolas Rivron from Hubrecht Institute, Netherlands, and are available from the Broad Bioimage Benchmark Collection ( ). The underlying measurements may be downloaded as S1 File. (F) Examples of analysis that can be done by CellProfiler: (top) cell volume relative nucleus volume, (middle) GAPDH transcript quantity in each cell using CellProfiler’s “RelateObjects” module, (bottom) number of GAPDH transcripts in Z-plane (bin size = 2.5 μm). (E) Segmentation of GAPDH transcript foci using CellProfiler, as viewed in Fiji. (D) Segmentation of cells after setting nuclei as seeds by CellProfiler, as viewed in Fiji. (C) Nuclei after segmentation by CellProfiler, as viewed in Fiji. Figure labels: RH (“RemoveHoles”), Close (“Closing”), Erode (“Erosion”), Mask (“MaskImage”), Math (“ImageMath”), EorS Features (“EnhanceOrSuppressFeatures”). (B) CellProfiler 3.0 image processing modules used for membrane image processing. (A) Original 3D image of blastocyst cell membrane prior to analysis. Images were captured of a mouse embryo blastocyst cell membrane stained with WGA and FISH for GAPDH transcripts.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |