Quantitative Image Analysis provides an objective assessment of staining intensity and tissue size or shape differences within your cohort of samples. We work closely with you to understand the nature of your study and provide a path towards obtaining standardized results and statistical analysis that can reveal numerous quantitative features of interest, usually exemplified by the percent of cells positive for a particular biomarker within your sections. We can also identify and quantitatively measure distinct tissue regions by training and applying machine learning classifiers to provide a deeper understanding of the changes in your tissue due to tumor growth, stromal infiltration, or necrotic foci formation.
Our laboratory offers serial sectioning of tissues for IHC immunostaining with distinct biomarkers; we have developed methods for intensity-based image alignment of multiple tissue sections to provide a "virtual multiplex" image, permitting the evaluation of regional distributions of multiple biomarkers. In addition to brightfield IHC analysis, we also offer customized quantitative analysis of highly multiplex imaging datasets, including for Imaging Mass Cytometry, Multiplexed Ion Beam Imaging, Co-Detection by indEXing, or Multiplex Immunofluorescence data. Services include customized and rapid development of cellular segmentation algorithms, as well as phenotypic analysis, t-SNE and UMAP dimensionality reduction, and clustering, and manual identification of cell types of interest.
We have more than 20 years of image analysis experience and provide rapid turnaround of results. Please reach out to us at email@example.com for a free consultation to learn more about what we can do for you.
Assess the number of positive cells for particular markers within distinct tissue areas
Quantify differences within specific cellular subcompartments (e.g. Nuclear to Cytoplasmic Ratio)
Break Whole Slide area into biologically relevant subregions (e.g. Tumor from Necrosis)
Measure differences in biomarker intensity & staining area
Provide objective assessment of differences between samples and treatment groups