Review



matlab-based automated scoring algorithm  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    MathWorks Inc matlab-based automated scoring algorithm
    Matlab Based Automated Scoring Algorithm, 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/matlab-based automated scoring algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based automated scoring algorithm - by Bioz Stars, 2026-03
    90/100 stars

    Images



    Similar Products

    matlab-based automated scoring algorithm  (MathWorks Inc)
    90
    MathWorks Inc matlab-based automated scoring algorithm
    Matlab Based Automated Scoring Algorithm, 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/matlab-based automated scoring algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based automated scoring algorithm - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    matlab-based semi-automated rgc counting algorithm  (MathWorks Inc)
    90
    MathWorks Inc matlab-based semi-automated rgc counting algorithm
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Matlab Based Semi Automated Rgc Counting Algorithm, 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/matlab-based semi-automated rgc counting algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based semi-automated rgc counting algorithm - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    matlab-based automated detection algorithm  (MathWorks Inc)
    90
    MathWorks Inc matlab-based automated detection algorithm
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Matlab Based Automated Detection Algorithm, 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/matlab-based automated detection algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based automated detection algorithm - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    matlab-based automated peak-picking algorithm  (MathWorks Inc)
    90
    MathWorks Inc matlab-based automated peak-picking algorithm
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Matlab Based Automated Peak Picking Algorithm, 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/matlab-based automated peak-picking algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based automated peak-picking algorithm - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    automated peak detection algorithm matlab r2019b  (MathWorks Inc)
    90
    MathWorks Inc automated peak detection algorithm matlab r2019b
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Automated Peak Detection Algorithm Matlab R2019b, 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/automated peak detection algorithm matlab r2019b/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    automated peak detection algorithm matlab r2019b - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    automated algorithm matlab  (MathWorks Inc)
    90
    MathWorks Inc automated algorithm matlab
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Automated Algorithm Matlab, 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/automated algorithm matlab/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    automated algorithm matlab - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    ssde calculation by matlab segmentation-based automated ssde algorithm's predictions  (MathWorks Inc)
    90
    MathWorks Inc ssde calculation by matlab segmentation-based automated ssde algorithm's predictions
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Ssde Calculation By Matlab Segmentation Based Automated Ssde Algorithm's Predictions, 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/ssde calculation by matlab segmentation-based automated ssde algorithm's predictions/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    ssde calculation by matlab segmentation-based automated ssde algorithm's predictions - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    automated matlab image processing algorithms  (MathWorks Inc)
    90
    MathWorks Inc automated matlab image processing algorithms
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Automated Matlab Image Processing Algorithms, 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/automated matlab image processing algorithms/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    automated matlab image processing algorithms - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    semi-automated matlab algorithm  (MathWorks Inc)
    90
    MathWorks Inc semi-automated matlab algorithm
    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or <t>retinal</t> <t>ganglion</t> <t>cell</t> <t>(RGC)</t> loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .
    Semi Automated Matlab Algorithm, 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/semi-automated matlab algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    semi-automated matlab algorithm - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or retinal ganglion cell (RGC) loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .

    Journal: Nature Communications

    Article Title: Myeloid lineage C3 induces reactive gliosis and neuronal stress during CNS inflammation

    doi: 10.1038/s41467-025-58708-3

    Figure Lengend Snippet: a Diagram of experimental paradigm showing how eyes were either evaluated for synaptic pathology (left) via cross-sections or retinal ganglion cell (RGC) loss via flat mounts (right) on EAE d16 mice. b Representative image of flat-mounted retina with 12 regions selected for Brn3a + RGC quantification. Scale bar in full retina image = 500 μm, in high magnification counting fields scale bar = 20 μm. c Quantification of Brn3a + RGCs at peak EAE. N = 4 per experimental group. d Quantification of the integrated density of markers Syn1 (left) and PSD95 (right) in the inner plexiform layer of CFA vs GFAP-Cre animals at peak EAE. Signal intensity values are normalized to CFA control, with AU representing “arbitrary units”. N = 4 CFA, 10 GFAP-Cre − and 7 GFAP-Cre + mice. e Representative immunofluorescent staining of Syn1 (red) and PSD95 (green) in the inner and outer plexiform layers across GFAP-Cre experimental groups. Scale bar = 50 um. f Same as in e but evaluating synaptic markers in the inner plexiform layer of LysM-Cre + and LysM-Cre − mice. Values are normalized to the CFA only animals utilized in Fig. 5d. N = 4 CFA, 6 LysM-Cre − and 8 LysM-Cre + mice. g Representative immunofluorescent staining of Syn1 and PSD95 in LysM-Cre − vs LysM-Cre + mice. Scale bar = 50 um. All bar graphs presented as mean +/- SEM, with one-way ANOVAs adjusted for multiple comparisons. Source data are provided as a source data file. Figure 5a created in BioRender. Smith, M. (2025) https://BioRender.com/j21s335 .

    Article Snippet: Our MATLAB-based semi-automated RGC counting algorithm was used to determine RGC number in each mouse .

    Techniques: Control, Staining