Search results for "Quantitative immunohistochemistry"
showing 2 items of 2 documents
Patterns of oncogene co-expression at single cell resolution in cancer influence survival
2020
AbstractBackgroundCancers often overexpress multiple clinically relevant oncogenes. However, it is not known if multiple oncogenes within a cancer combine uniquely in specific cellular sub-populations to influence clinical outcome. We studied this phenomenon using the prognostically relevant oncogenes MYC, BCL2 and BCL6 in Diffuse Large B-Cell Lymphoma (DLBCL).MethodsQuantitative multispectral imaging simultaneously measured oncogene co-expression at single-cell resolution in reactive lymphoid tissue (n=12) and four independent cohorts (n=409) of DLBCL. Mathematically derived co-expression phenotypes were evaluated in DLBCLs with immunohistochemistry (n=316) and eight DLBCL cohorts with gen…
Blood Vessel Detection Algorithm for Tissue Engineering and Quantitative Histology.
2021
AbstractImmunohistochemistry for vascular network analysis plays a fundamental role in basic science, translational research and clinical practice. However, identifying vascularization in histological tissue images is time consuming and markedly depends on the operator’s experience. In this study, we present “blood vessel detection—BVD”, an automatic algorithm for quantitative analysis of blood vessels in immunohistochemical images. BVD is based on extraction and analysis of low-level image features and spatial filtering techniques, which do not require a training phase. BVD algorithm performance was comparatively evaluated on histological sections from three different in vivo experiments. …