Image and Slide Analysis Services

In recent decades, the increase in computing power and the development of automated microscopes and high-performance slide scanners have revolutionized the field of bioimaging. With the ability to process vast amounts of data, researchers are now able to glean new insights and drive innovation in their respective fields. However, the complexity of analyzing such large datasets requires expertise in both biology and computer science. At Visikol, we provide quantitative image and data analysis services for high content and whole slide image datasets, either as a standalone service or in conjunction with our assay and tissue imaging services. With our cutting-edge technology and experienced team, we routinely process terabytes of images per day, ensuring that no project is too large or small. Let us help you unlock the potential of your biological imaging data and take your research to the next level.

Discuss with our scientists

We understand that every project is unique, and that’s why we take the time to work closely with our clients to define their specific needs and objectives. Our goal is to ensure that we accurately measure and quantify the parameters that are most important to you.

Upload your data to our server

For handling client data, our servers use state-of-the-art security protocols, including 256-bit encryption, to ensure the privacy and security of client data.

Image analysis

Our image analysis services are designed to provide clients with the most accurate and reliable results possible. To achieve this, we utilize a range of cutting-edge image analysis tools, including our own custom-built Nitropixelin library, as well as industry established tools such as ImageJ, CellProfiler, and a variety of Python libraries such as Sci-kit Learn, SimpleITK, NumPy, Pandas, and many more. Our Nitropixelin library is specifically designed to process multi-gigabyte image sets, such as high content imaging data, confocal stacks, and whole slide images.

Reporting

At Visikol, we believe that clear and concise reporting is key to helping you draw accurate conclusions and understand the trends seen in big datasets, which is why we provide a comprehensive report that outlines our methodology and results in an easy-to-understand format. As a part of our reporting process, we provide clients with a written report along with any relevant data, which can be delivered via the cloud or a shipped drive for your convenience.

Quantification of positive cells for immunohistochemistry

Analysis of immune cell population within and outside of tumor for immuno-oncology

Analysis of spatial relationships between cell types

Image Analysis Endpoints

Bioinformatics Service

Our comprehensive approach, which includes techniques such as principal component analysis, feature selection, clustering, correlograms, heatmaps, and more, enables you to gain valuable insights and make data-driven decisions.

Biomarker Quantification Colocalization

Quantification of area/volume or number of cells exhibiting biomarker expression, and colocalization of biomarkers to identify subtypes.

Biomolecule / Antibody Penetration

Assessment of biological/antibody penetration into tissue/3D cell culture models to evaluate changes in pharmacokinetic distribution due to modifications (e.g. drug conjugation).

Blood vessel segmentation and analysis

Segmentation of blood vessels and quantification of area/volume, branching patterns, branch orientation, tortuosity, and cellular proximity.

Cell Counting

Quantification of cells by type, and analysis of cell population by size, shape, or distribution of cells. With immunofluorescence, quantify multiple cell populations simultaneously to evaluate distribution of cell types within tissues.

Immune cell population analysis

Quantification of immune cell population in and around tumor region for evaluation of immuno-oncology treatments. Spatial analysis and nearest-neighbor analysis of immune cell subtypes.

Machine Learning Classification

Use of deep learning to classify image data based on training dataset for characterization and categorization of tissues/cells.

Machine Learning Segmentation

Our Machine Learning Segmentation Services utilize classical or deep learning techniques based on supervised machine learning.

Morphometric Analysis

Our comprehensive approach enables you to gain deep insights into size, shape, texture, granularity, and other essential morphological parameters.

Orientation Analysis

Quantitatively assess orientation of cell types or structures in imaging data to evaluate homogeneity/heterogeneity of structural orientation within bio-imaging data.