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coltapp application  (MathWorks Inc)


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    Structured Review

    MathWorks Inc coltapp application
    <t>ColTapp</t> graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .
    Coltapp Application, 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/result/coltapp application/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    coltapp application - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application"

    Article Title: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

    Journal: Scientific Reports

    doi: 10.1038/s41598-020-72979-4

    ColTapp graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .
    Figure Legend Snippet: ColTapp graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .

    Techniques Used: Imaging

    Comparison with other colony image analysis tools.
    Figure Legend Snippet: Comparison with other colony image analysis tools.

    Techniques Used: Comparison



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    coltapp application  (MathWorks Inc)
    90
    MathWorks Inc coltapp application
    <t>ColTapp</t> graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .
    Coltapp Application, 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/result/coltapp application/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    coltapp application - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    ColTapp graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .

    Journal: Scientific Reports

    Article Title: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

    doi: 10.1038/s41598-020-72979-4

    Figure Lengend Snippet: ColTapp graphical user interface and analysis workflow. ( a ) For visualization, results are overlaid onto the images: typically, the circles representing detected colonies and the edges of the Voronoi tessellation shown here in blue on the image. The main analysis panel, on the left of the image, is separated in three tabs. Here the Detect tab, which allows the user to detect colonies on a plate, is visualized. The Main tab, which allows the user to analyze either time-lapse or endpoint images and the Visualize tab are displayed on the Supplementary Fig. . ( b ) Schematic of simple image acquisition setups including a camera holder. An Arduino board (blue icon) can be used to trigger the camera automatically for time-lapse imaging of a plate ( , Image acquisition, for implementation). ColTapp operates in two modes: either Time-lapse (TL) or Endpoint (EP) mode, depending on input data, illustrated by the two different folders (turquoise and yellow respectively). The turquoise highlighted functionalities are specific to the Time-lapse mode, while the yellow highlighted ones are specific to Endpoint mode. In the middle, the green highlighted functionalities are common to both modes. Note that each step of the workflow (apart from the two which are detailed in the following sections) has a corresponding section in the Supplementary text, which may serve as a guide to the user. For example, the “Analysis set-up” is described in the Supplementary text : a user may define the area of analysis on its images, as shown here in turquoise on the 3 example images. The implementation of the “colony detection” and “radius tracking over time” algorithms are described in the and illustrated here with small subsets of Figs. and respectively. The colony characteristics are illustrated here with a small subset of the Supplementary Fig. .

    Article Snippet: We programmed the ColTapp application with MATLAB 2020a (MathWorks).

    Techniques: Imaging

    Comparison with other colony image analysis tools.

    Journal: Scientific Reports

    Article Title: Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application

    doi: 10.1038/s41598-020-72979-4

    Figure Lengend Snippet: Comparison with other colony image analysis tools.

    Article Snippet: We programmed the ColTapp application with MATLAB 2020a (MathWorks).

    Techniques: Comparison