otsu clustering thresholding process Search Results


drgquant pipeline  (Oxford Instruments)
99
Oxford Instruments drgquant pipeline
<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).
Drgquant Pipeline, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/drgquant pipeline/product/Oxford Instruments
Average 99 stars, based on 1 article reviews
drgquant pipeline - by Bioz Stars, 2026-05
99/100 stars
  Buy from Supplier
multi-otsu thresholding algorithm  (Simpleware Ltd)
90
Simpleware Ltd multi-otsu thresholding algorithm
<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).
Multi Otsu Thresholding Algorithm, supplied by Simpleware Ltd, 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/multi-otsu thresholding algorithm/product/Simpleware Ltd
Average 90 stars, based on 1 article reviews
multi-otsu thresholding algorithm - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
otsu thresholding  (GraphPad Software Inc)
90
GraphPad Software Inc otsu thresholding
<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).
Otsu Thresholding, supplied by GraphPad Software 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/otsu thresholding/product/GraphPad Software Inc
Average 90 stars, based on 1 article reviews
otsu thresholding - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
dan thresholding otsu  (Teknik Hizmetler)
86
Teknik Hizmetler dan thresholding otsu
<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).
Dan Thresholding Otsu, supplied by Teknik Hizmetler, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dan thresholding otsu/product/Teknik Hizmetler
Average 86 stars, based on 1 article reviews
dan thresholding otsu - by Bioz Stars, 2026-05
86/100 stars
  Buy from Supplier
additional glimmer(ct) predictions  (Critica LLC)
90
Critica LLC additional glimmer(ct) predictions
<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).
Additional Glimmer(ct) Predictions, supplied by Critica LLC, 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/additional glimmer(ct) predictions/product/Critica LLC
Average 90 stars, based on 1 article reviews
additional glimmer(ct) predictions - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
logistic regression by proc logit  (SAS institute)
90
SAS institute logistic regression by proc logit
Melanoma skin cancer publications using deep learning method.
Logistic Regression By Proc Logit, supplied by SAS institute, 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/logistic regression by proc logit/product/SAS institute
Average 90 stars, based on 1 article reviews
logistic regression by proc logit - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
cellprofiler software  (Broad Institute Inc)
90
Broad Institute Inc cellprofiler software
Melanoma skin cancer publications using deep learning method.
Cellprofiler Software, supplied by Broad Institute 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/cellprofiler software/product/Broad Institute Inc
Average 90 stars, based on 1 article reviews
cellprofiler software - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
ovonic threshold switch (ots) elements  (Nanoelectronics Research Corporation)
90
Nanoelectronics Research Corporation ovonic threshold switch (ots) elements
Melanoma skin cancer publications using deep learning method.
Ovonic Threshold Switch (Ots) Elements, supplied by Nanoelectronics Research Corporation, 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/ovonic threshold switch (ots) elements/product/Nanoelectronics Research Corporation
Average 90 stars, based on 1 article reviews
ovonic threshold switch (ots) elements - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
tissue segmentation with otsu thresholding  (Lunit Inc)
90
Lunit Inc tissue segmentation with otsu thresholding
Melanoma skin cancer publications using deep learning method.
Tissue Segmentation With Otsu Thresholding, supplied by Lunit 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/tissue segmentation with otsu thresholding/product/Lunit Inc
Average 90 stars, based on 1 article reviews
tissue segmentation with otsu thresholding - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
visiopharm software  (Visiopharm AS)
90
Visiopharm AS visiopharm software
Melanoma skin cancer publications using deep learning method.
Visiopharm Software, supplied by Visiopharm AS, 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/visiopharm software/product/Visiopharm AS
Average 90 stars, based on 1 article reviews
visiopharm software - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
otsu algorithm-defined nature biotechnology article  (Nature Biotechnology)
90
Nature Biotechnology otsu algorithm-defined nature biotechnology article
Melanoma skin cancer publications using deep learning method.
Otsu Algorithm Defined Nature Biotechnology Article, supplied by Nature Biotechnology, 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/otsu algorithm-defined nature biotechnology article/product/Nature Biotechnology
Average 90 stars, based on 1 article reviews
otsu algorithm-defined nature biotechnology article - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier
otsu thresholding method  (CH Instruments)
90
CH Instruments otsu thresholding method
Melanoma skin cancer publications using deep learning method.
Otsu Thresholding Method, supplied by CH Instruments, 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/otsu thresholding method/product/CH Instruments
Average 90 stars, based on 1 article reviews
otsu thresholding method - by Bioz Stars, 2026-05
90/100 stars
  Buy from Supplier

Image Search Results


DRGquant Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: DRGquant Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Staining

LPS induced macrophage activation in our pipeline comparison. (A) Representative images of macrophages 24 h after intrathecal saline or LPS in wild type C57BL/6 mice and Ccr2 −/− mice. Scale bar 20 μm. (B) LPS induces an increase in the volume over macrophages over total volume of the sample in both wild type and Ccr2 −/− mice, Analysis performed with Imaris. (C) Automated analysis with our pipeline shows consistent results with Imaris. (D) No difference is observed between PV and NPV macrophages in macrophage numbers. (E) Using DRGquant we can see that individual macrophages increase in size following IT-LPS in both wild type and CCR2KO mice (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ***P < 0.001, **** P < 0.0001, ns = not significant, number of mice: Wt_saline=6, Wt_LPS=6, CCR2 −/ _saline=3,CCR2 −/− _LPS=3, 2 DRGs per mouse).

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: LPS induced macrophage activation in our pipeline comparison. (A) Representative images of macrophages 24 h after intrathecal saline or LPS in wild type C57BL/6 mice and Ccr2 −/− mice. Scale bar 20 μm. (B) LPS induces an increase in the volume over macrophages over total volume of the sample in both wild type and Ccr2 −/− mice, Analysis performed with Imaris. (C) Automated analysis with our pipeline shows consistent results with Imaris. (D) No difference is observed between PV and NPV macrophages in macrophage numbers. (E) Using DRGquant we can see that individual macrophages increase in size following IT-LPS in both wild type and CCR2KO mice (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ***P < 0.001, **** P < 0.0001, ns = not significant, number of mice: Wt_saline=6, Wt_LPS=6, CCR2 −/ _saline=3,CCR2 −/− _LPS=3, 2 DRGs per mouse).

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Activation Assay, Comparison, Saline

Uptake of fluorophore labeled dextran. (A) Representative sum z stack images of naïve (top) and 24 h following IT LPS injected (bottom) whole mount DRGs stained with Iba1 for macrophages, dextran, and CD31 for blood vessels. Scale bar 20 μm (B) Mean intensity of dextran within individual macrophages in the DRGs of naïve or IT LPS injected mice (one way ANOVA with Tukey post hoc test, means and individual macrophages are shown; **** P < 0.0001). (C) 3D reconstruction of single macrophage with 3D ROI of DRGquant output outline in green and dextran in blue, showing subcellular spatial resolution. Scale bar is 5 μm.

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: Uptake of fluorophore labeled dextran. (A) Representative sum z stack images of naïve (top) and 24 h following IT LPS injected (bottom) whole mount DRGs stained with Iba1 for macrophages, dextran, and CD31 for blood vessels. Scale bar 20 μm (B) Mean intensity of dextran within individual macrophages in the DRGs of naïve or IT LPS injected mice (one way ANOVA with Tukey post hoc test, means and individual macrophages are shown; **** P < 0.0001). (C) 3D reconstruction of single macrophage with 3D ROI of DRGquant output outline in green and dextran in blue, showing subcellular spatial resolution. Scale bar is 5 μm.

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Labeling, Injection, Staining

Melanoma skin cancer publications using deep learning method.

Journal: Frontiers in Medicine

Article Title: Artificial Intelligence in Cutaneous Oncology

doi: 10.3389/fmed.2020.00318

Figure Lengend Snippet: Melanoma skin cancer publications using deep learning method.

Article Snippet: Kefel et al. ( ) , Automatic method for detection of pink blush (common feature in BCC) Manually created borders vs. automatic created borders , Manual AUC: 87.8% Automatic AUC: 87.7% , Border detection by GAC and modified Otsu's threshold Classification: logistic regression by Proc Logit of SAS (smoothness, brightness) , n = 2,266 dermoscopic images manually created borders n_train = 354 n_test = 1,024 GAC n_train = 888 n_test = 1,024.

Techniques: Extraction

Non-melanoma skin cancer publications using conventional machine learning method.

Journal: Frontiers in Medicine

Article Title: Artificial Intelligence in Cutaneous Oncology

doi: 10.3389/fmed.2020.00318

Figure Lengend Snippet: Non-melanoma skin cancer publications using conventional machine learning method.

Article Snippet: Kefel et al. ( ) , Automatic method for detection of pink blush (common feature in BCC) Manually created borders vs. automatic created borders , Manual AUC: 87.8% Automatic AUC: 87.7% , Border detection by GAC and modified Otsu's threshold Classification: logistic regression by Proc Logit of SAS (smoothness, brightness) , n = 2,266 dermoscopic images manually created borders n_train = 354 n_test = 1,024 GAC n_train = 888 n_test = 1,024.

Techniques: Generated, Modification