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run3dmorph  (MathWorks Inc)


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    MathWorks Inc run3dmorph
    Visual pipeline illustrating the steps involved in 3D mesh extraction using the <t>run3dmorph</t> software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).
    Run3dmorph, 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/run3dmorph/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    run3dmorph - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera"

    Article Title: Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

    Journal: Philosophical Transactions of the Royal Society B: Biological Sciences

    doi: 10.1098/rstb.2015.0227

    Visual pipeline illustrating the steps involved in 3D mesh extraction using the run3dmorph software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).
    Figure Legend Snippet: Visual pipeline illustrating the steps involved in 3D mesh extraction using the run3dmorph software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).

    Techniques Used: Extraction, Software

    Illustration of idealized base shapes, used by run3dmorph for estimating surface area and volume of the complete object. ( a ) Irregular cone base; ( b ) irregular cylinder base; ( c ) spheroidal dome base.
    Figure Legend Snippet: Illustration of idealized base shapes, used by run3dmorph for estimating surface area and volume of the complete object. ( a ) Irregular cone base; ( b ) irregular cylinder base; ( c ) spheroidal dome base.

    Techniques Used:

    Visual comparison of data types: Tohoku University 3D specimens from CT and semi-3D half-hulls extracted using the run3dmorph software on stacked microscopic images. Three examples specimens are shown: Trilobatus sacculifer , Truncorotalia truncatulinoides and Neogloboquadrina dutertrei . The Tohoku University specimens were digitized using X-ray CT at 5 µm resolution. Run3dmorph -extracted 3D-meshes are shown next to their corresponding focused 2D-image.
    Figure Legend Snippet: Visual comparison of data types: Tohoku University 3D specimens from CT and semi-3D half-hulls extracted using the run3dmorph software on stacked microscopic images. Three examples specimens are shown: Trilobatus sacculifer , Truncorotalia truncatulinoides and Neogloboquadrina dutertrei . The Tohoku University specimens were digitized using X-ray CT at 5 µm resolution. Run3dmorph -extracted 3D-meshes are shown next to their corresponding focused 2D-image.

    Techniques Used: Comparison, Software

    Exploration of the reproducibility tests of the Orbulina universa individual ( a ) The PC1 versus PC2 coordinates for O. universa from <xref ref-type=figure 8 c . The points highlighted in red are outliers for which the run3dmorph -extracted semi-3D half-hulls exhibited pathologies (see text). ( b – d ) Extracted mesh, focused image and height map showcasing pathologies arising during z -stack focusing. In ( c ), the smeared, unfocused portions of the object are outlined in white. ( e – g ) The corresponding mesh, focused image and height map for a properly extracted O. orbulina individual. " title="... highlighted in red are outliers for which the run3dmorph -extracted semi-3D half-hulls exhibited pathologies (see text). ( ..." property="contentUrl" width="100%" height="100%"/>
    Figure Legend Snippet: Exploration of the reproducibility tests of the Orbulina universa individual ( a ) The PC1 versus PC2 coordinates for O. universa from figure 8 c . The points highlighted in red are outliers for which the run3dmorph -extracted semi-3D half-hulls exhibited pathologies (see text). ( b – d ) Extracted mesh, focused image and height map showcasing pathologies arising during z -stack focusing. In ( c ), the smeared, unfocused portions of the object are outlined in white. ( e – g ) The corresponding mesh, focused image and height map for a properly extracted O. orbulina individual.

    Techniques Used:



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    run3dmorph  (MathWorks Inc)
    90
    MathWorks Inc run3dmorph
    Visual pipeline illustrating the steps involved in 3D mesh extraction using the <t>run3dmorph</t> software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).
    Run3dmorph, 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/run3dmorph/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    run3dmorph - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Visual pipeline illustrating the steps involved in 3D mesh extraction using the run3dmorph software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).

    Journal: Philosophical Transactions of the Royal Society B: Biological Sciences

    Article Title: Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

    doi: 10.1098/rstb.2015.0227

    Figure Lengend Snippet: Visual pipeline illustrating the steps involved in 3D mesh extraction using the run3dmorph software. ( a ) Z -stacks of each individual object (taken at varying focal planes of known height above the object) are processed using the Stack Focuser plug-in for ImageJ/FIJI , resulting in a focused image of the object and a height map (built using an 11 × 11 pixel kernel size). ( b ) The focused image and height map are rescaled such that each pixel has a height and width of 1 µm, and the 2D outline of the focused image is extracted using the run2dmorph software (see https://github.com/Hull-Lab ). Each pixel of the binary 2D outline image is then multiplied against the corresponding pixel in the height map (element-wise multiplication). This effectively deletes background noise and results in a cleaned-up height map ( c ). The greyscale value of each pixel in the height map is then used, in conjunction with the distance between each z -stack slice, to back-calculate the real-world height of each pixel and generate an unfiltered 3D mesh ( d ). High and low outlier noise is then filtered from the 3D mesh using a custom neighbourhood pixel-averaging algorithm (using a user-defined n × n pixel kernel, where n is a positive odd integer). Vertex and face coordinates are then extracted from the cleaned 3D mesh and outputted in standard 3D ASCII formats (OBJ and OFF).

    Article Snippet: The first two components of the pipeline ( segment and focus ) are written in Python, a free programming language that runs across platforms. run2dmorph and run3dmorph currently execute in MATLAB (version 2015b or above), a proprietary software, but will be ported into Python in future versions.

    Techniques: Extraction, Software

    Illustration of idealized base shapes, used by run3dmorph for estimating surface area and volume of the complete object. ( a ) Irregular cone base; ( b ) irregular cylinder base; ( c ) spheroidal dome base.

    Journal: Philosophical Transactions of the Royal Society B: Biological Sciences

    Article Title: Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

    doi: 10.1098/rstb.2015.0227

    Figure Lengend Snippet: Illustration of idealized base shapes, used by run3dmorph for estimating surface area and volume of the complete object. ( a ) Irregular cone base; ( b ) irregular cylinder base; ( c ) spheroidal dome base.

    Article Snippet: The first two components of the pipeline ( segment and focus ) are written in Python, a free programming language that runs across platforms. run2dmorph and run3dmorph currently execute in MATLAB (version 2015b or above), a proprietary software, but will be ported into Python in future versions.

    Techniques:

    Visual comparison of data types: Tohoku University 3D specimens from CT and semi-3D half-hulls extracted using the run3dmorph software on stacked microscopic images. Three examples specimens are shown: Trilobatus sacculifer , Truncorotalia truncatulinoides and Neogloboquadrina dutertrei . The Tohoku University specimens were digitized using X-ray CT at 5 µm resolution. Run3dmorph -extracted 3D-meshes are shown next to their corresponding focused 2D-image.

    Journal: Philosophical Transactions of the Royal Society B: Biological Sciences

    Article Title: Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

    doi: 10.1098/rstb.2015.0227

    Figure Lengend Snippet: Visual comparison of data types: Tohoku University 3D specimens from CT and semi-3D half-hulls extracted using the run3dmorph software on stacked microscopic images. Three examples specimens are shown: Trilobatus sacculifer , Truncorotalia truncatulinoides and Neogloboquadrina dutertrei . The Tohoku University specimens were digitized using X-ray CT at 5 µm resolution. Run3dmorph -extracted 3D-meshes are shown next to their corresponding focused 2D-image.

    Article Snippet: The first two components of the pipeline ( segment and focus ) are written in Python, a free programming language that runs across platforms. run2dmorph and run3dmorph currently execute in MATLAB (version 2015b or above), a proprietary software, but will be ported into Python in future versions.

    Techniques: Comparison, Software

    Exploration of the reproducibility tests of the Orbulina universa individual ( a ) The PC1 versus PC2 coordinates for O. universa from <xref ref-type=figure 8 c . The points highlighted in red are outliers for which the run3dmorph -extracted semi-3D half-hulls exhibited pathologies (see text). ( b – d ) Extracted mesh, focused image and height map showcasing pathologies arising during z -stack focusing. In ( c ), the smeared, unfocused portions of the object are outlined in white. ( e – g ) The corresponding mesh, focused image and height map for a properly extracted O. orbulina individual. " width="100%" height="100%">

    Journal: Philosophical Transactions of the Royal Society B: Biological Sciences

    Article Title: Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

    doi: 10.1098/rstb.2015.0227

    Figure Lengend Snippet: Exploration of the reproducibility tests of the Orbulina universa individual ( a ) The PC1 versus PC2 coordinates for O. universa from figure 8 c . The points highlighted in red are outliers for which the run3dmorph -extracted semi-3D half-hulls exhibited pathologies (see text). ( b – d ) Extracted mesh, focused image and height map showcasing pathologies arising during z -stack focusing. In ( c ), the smeared, unfocused portions of the object are outlined in white. ( e – g ) The corresponding mesh, focused image and height map for a properly extracted O. orbulina individual.

    Article Snippet: The first two components of the pipeline ( segment and focus ) are written in Python, a free programming language that runs across platforms. run2dmorph and run3dmorph currently execute in MATLAB (version 2015b or above), a proprietary software, but will be ported into Python in future versions.

    Techniques: