quantcenter nuclear (sox10) algorithm  (3DHistech ltd)

Journal: bioRxiv

Article Title: Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

doi: 10.1101/2025.05.16.654590

Figure Lengend Snippet:

Article Snippet: For example, Balazs et al. assessed Ki67 expression using HALO, QuantCenter (3DHistech), and QuPath, demonstrating excellent reproducibility both within and across digital image analysis platforms [ ].

Techniques: Comparison

Journal: bioRxiv

Article Title: Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

doi: 10.1101/2025.05.16.654590

Figure Lengend Snippet: Prostate cancer TMAs were stained with antibody panel 1 (CD3, CD8, PD-1, PD-L1, FoxP3, pCK), or with antibody panel 2 (CD20, CD103, Delta-TCR, TIM3, CD164, pCK). Scanned mIF images were analyzed using either QuPath or HALO image analysis software packages. The processing of images encompasses multiple steps, including tissue segmentation, cell detection, and quantification of immune cell populations. Quantitative measures of tumor regions and immune cell percentages can be obtained through analysis with HALO or QuPath, but unsupervised neighborhood analysis is only possible using a combination of QuPath and CytoMap.

Article Snippet: For example, Balazs et al. assessed Ki67 expression using HALO, QuantCenter (3DHistech), and QuPath, demonstrating excellent reproducibility both within and across digital image analysis platforms [ ].

Techniques: Staining, Software

Journal: bioRxiv

Article Title: Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

doi: 10.1101/2025.05.16.654590

Figure Lengend Snippet: A . Panel 1, composed of antibodies reactive with PD1, CD8, CD3, PDL1, FoxP3, and pCK. B . Pearson correlation analysis between QuPath and HALO using the same signal intensity thresholds in HALO and QuPath to distinguish positive and negative pixels for analysis. C . Panel 2, encompassing markers TIM3, CD20, CD103, CD164, Delta-TCR, and pCK. D . Pearson correlation analysis between QuPath and HALO using the same signal intensity thresholds in HALO and QuPath to distinguish positive and negative pixels for analysis.

Article Snippet: For example, Balazs et al. assessed Ki67 expression using HALO, QuantCenter (3DHistech), and QuPath, demonstrating excellent reproducibility both within and across digital image analysis platforms [ ].

Techniques:

Journal: bioRxiv

Article Title: Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

doi: 10.1101/2025.05.16.654590

Figure Lengend Snippet: Comparison of infiltration analysis by HALO and QuPath. A. Tumor expansion of 20µm in HALO and QuPath. B. Linear fitting of scattering plot between HALO and QuPath output

Article Snippet: For example, Balazs et al. assessed Ki67 expression using HALO, QuantCenter (3DHistech), and QuPath, demonstrating excellent reproducibility both within and across digital image analysis platforms [ ].

Techniques: Comparison

Journal: bioRxiv

Article Title: Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

doi: 10.1101/2025.05.16.654590

Figure Lengend Snippet: Comparison of nearest neighbor analysis by HALO and QuPath. A. Illustration of nearest neighbor analysis in HALO. B. Linear fitting of scatter plot between HALO and QuPath outputs.

Article Snippet: For example, Balazs et al. assessed Ki67 expression using HALO, QuantCenter (3DHistech), and QuPath, demonstrating excellent reproducibility both within and across digital image analysis platforms [ ].

Techniques: Comparison