QUANTITATIVE
IMAGE ANALYSIS

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 info@histowiz.com for a free consultation to learn more about what we can do for you.

Region of Interest Classification:

Machine Learning / AI Classifier Training

Separate Tumor From Necrosis
Identify Glomeruli and Tubules in Kidney
Pancreatic Tumor / Stroma / Islet Segmentation
Colon Epithelium from Lamina Propria Segmentation
TMA-based Segmentation
Skin Epidermis / Layers of Dermis Segmentation
Brain Atlas-based Segmentation

Cellular or Area based IHC / IF Quantification:

% Positive Biomarkers on Cell / Sub-compartment basis:

Co-registration of serial brightfield IHC sections using intensity-based image alignment
Tumor Invading Lymphocyte (IHC & mxIF), plus distance analysis
Fatty Acid accumulation / NASH studies in liver
Muscle Fiber / Adipocyte size distribution analysis
Spleen Highly Multiplexed cellular phenotyping
Concentric partitioning / distance-based vessel and tumor edge analysis