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image processing toolbox 2 matlab v2019a  (MathWorks Inc)


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    MathWorks Inc image processing toolbox 2 matlab v2019a
    VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the <t>MATLAB</t> function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).
    Image Processing Toolbox 2 Matlab V2019a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2714 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/image processing toolbox 2 matlab v2019a/product/MathWorks Inc
    Average 96 stars, based on 2714 article reviews
    image processing toolbox 2 matlab v2019a - by Bioz Stars, 2026-06
    96/100 stars

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    1) Product Images from "VistoSeg : Processing utilities for high-resolution images for spatially resolved transcriptomics data"

    Article Title: VistoSeg : Processing utilities for high-resolution images for spatially resolved transcriptomics data

    Journal: Biological Imaging

    doi: 10.1017/S2633903X23000235

    VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the MATLAB function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).
    Figure Legend Snippet: VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the MATLAB function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).

    Techniques Used: Staining



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    image processing toolbox 2 matlab v2019a  (MathWorks Inc)
    96
    MathWorks Inc image processing toolbox 2 matlab v2019a
    VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the <t>MATLAB</t> function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).
    Image Processing Toolbox 2 Matlab V2019a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/image processing toolbox 2 matlab v2019a/product/MathWorks Inc
    Average 96 stars, based on 1 article reviews
    image processing toolbox 2 matlab v2019a - by Bioz Stars, 2026-06
    96/100 stars
    		  Buy from Supplier

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    VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the MATLAB function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).

    Journal: Biological Imaging

    Article Title: VistoSeg : Processing utilities for high-resolution images for spatially resolved transcriptomics data

    doi: 10.1017/S2633903X23000235

    Figure Lengend Snippet: VistoSeg workflow for Visium H&E image segmentation. (a) Raw histology image of human dorsolateral prefrontal cortex. (b) Gaussian smoothed and contrast-adjusted image of the raw histology image in (a). (c) Enhanced image from (b) converted from RGB color space to L*a*b color space. (d) Different color gradients (k = 5) identified by the MATLAB function imsegkmeans applied to the raw histology image. Cluster 3 corresponded to the nuclei, stained blue in the raw histology image. (d’) An inset of nuclei cluster 3 in (d). (e) Output of refineVNS from nuclei cluster 3 (d’). The refineVNS function allows for separation of adjacent nuclei. (f) Final binary nuclei segmentation obtained from (e).

    Article Snippet: Project name: VistoSeg Project home page: https://github.com/LieberInstitute/VistoSeg , http://research.libd.org/VistoSeg/ Operating system(s): MAC, Windows, LINUX Programming language: MATLAB Other requirements: (1) MATLAB Image Processing Toolbox (2) MATLAB v2019a or later (3) Minimum ~ (3*raw image) 80 GB RAM for the initial ( splitSlide ) step and <16GB for all the remaining steps (4) SpaceRanger (10× Genomics) v1.0 or higher (5) Loupe browser (10× Genomics) v5 or higher License: GNU GENERAL PUBLIC LICENSE, Version 3, June 29, 2007.

    Techniques: Staining