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euclidean distance transform of hyphae (matlab function bwdist)  (MathWorks Inc)


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    MathWorks Inc euclidean distance transform of hyphae (matlab function bwdist)
    Euclidean Distance Transform Of Hyphae (Matlab Function Bwdist), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+bwdist/pm38049892-233-21-22
    Average 90 stars, based on 1 article reviews
    euclidean distance transform of hyphae (matlab function bwdist) - by Bioz Stars, 2026-10
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    other:

    Article Title: Fluorescence Lifetime Imaging Microscopy (FLIM) reveals spatial-metabolic changes in 3D breast cancer spheroids.
    Article Snippet: After locating the centers, the distance transform was computed relative to the center pixels using the built-in MATLAB function bwdist to compute the 2D Euclidean distance transform44.

    Article Title: Nodal is a short-range morphogen with activity that spreads through a relay mechanism in human gastruloids
    Article Snippet: Cells were fixed in 4% paraformaldehyde for 15 min. smFISH was performed following manufacturer’s instructions (ACD Bio, RNAscope fluorescent multiplex assay), with indicated probes (Supplementary Table ).

    Article Title: Multiplexed GTPase and GEF biosensor imaging enables network connectivity analysis
    Article Snippet: To construct the sampling windows at a constant distance from the cell edge we computed a distance map (Matlab function: bwdist) to the segmented cell edge.

    Article Title: Dose-volume histogram prediction using density estimation.
    Article Snippet: The voxel size used for this set of patients was × ×1 1 1 mm3and the signed distance was computed using the MATLAB function bwdist (Maurer et al 2003) with a Euclidean distance measure.

    Crystallization Assay:

    Article Title: Development of a structure analysis algorithm on structures from CuCl2⋅2H2O crystallization with agricultural products
    Article Snippet: 0168-1699/$ see front matter 2012 Elsevier B.V. A http://dx.doi.org/10.1016/j.compag.2012.11.003 Abbreviations: ROI, region of interest; GLCM, grey q The work described in this article has been carrie uniform requirements for manuscripts submitted to b ⇑ Corresponding author.. Present address: Crystal L Kleefseweg 9, NL-6595NK Ottersum, The Netherlands E-mail address: p.doesburg@crystal-lab.nl (P. Does Crystallization patterns emerge when an aqueous dihydrate Copper chloride (CuCl2 2H2O) solution in the presence of organic additives (juices/extracts) is crystallized on a glass plate.. The emerging patterns are additive-specific and reflect physiological processes like maturation and ageing, the effect of processing, feeding regime and production system in a broad range of agricultural products.



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    MathWorks Inc bwdist matlab function
    Overview of binary classification models and corresponding <t> MATLAB </t> functions trained using the input data X (i.e. 20 dimensional multi-color space representation of manually segmented FLU+VIS plant and background regions) and the vector of region labels Y (i.e. Y=0 for background, Y=1 for plant image regions)
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    Overview of binary classification models and corresponding  MATLAB  functions trained using the input data X (i.e. 20 dimensional multi-color space representation of manually segmented FLU+VIS plant and background regions) and the vector of region labels Y (i.e. Y=0 for background, Y=1 for plant image regions)

    Journal: Plant Methods

    Article Title: A two-step registration-classification approach to automated segmentation of multimodal images for high-throughput greenhouse plant phenotyping

    doi: 10.1186/s13007-020-00637-x

    Figure Lengend Snippet: Overview of binary classification models and corresponding MATLAB functions trained using the input data X (i.e. 20 dimensional multi-color space representation of manually segmented FLU+VIS plant and background regions) and the vector of region labels Y (i.e. Y=0 for background, Y=1 for plant image regions)

    Article Snippet: Consequently, a set of classification models based on eight classifiers from Table was trained to detect small background (i.e. non-plant) structures on the basis of the object’s color ratios (R/B, R/G, G/B), size and vicinity to the largest image structure assessed by the Euclidean distance map using the bwdist MATLAB function.

    Techniques: Plasmid Preparation