Nikon releases four Add-on Modules dedicated to CL-Quant cell imaging analysis software
oct. 8, 2019
TOKYO - Nikon Corporation (Nikon) is pleased to announce the October 31 release of four Add-on Modules exclusively for CL-Quant image analysis software, which can non-invasively perform automatic cell identification and analysis without cell staining to support easier and more efficient cell evaluation in the areas of drug discovery research and regenerative medicine.
In order to aid cell-based research efforts in these fields, Nikon has developed the Cell Evaluation Solutions service which combines advanced imaging hardware technology for automated, non-invasive cell monitoring, with powerful, CL-Quant-based image evaluation software for unbiased, quantitative assessment of cell health, growth and morphology, which can be customized to meet individual customer’s needs.
Nikon will expand its Cell Evaluation Solutions services by adding four new Add-on Modules to the CL-Quant image analysis software, further increasing the range of non-invasive, in-line image analysis tools dedicated to the areas of drug discovery research and regenerative medicine.
Nikon will exhibit its new range of products at BioJapan 2019, held from October 9 through 11 at Pacifico Yokohama.
Name of Product
Counts mesenchymal stem cells (MSCs) based on phase-contrast images. Requires no cell staining, enabling non-invasive analysis of cell proliferation conditions.
Measures cell migration into an in vitro wound/scratch* using phase-contrast images. Automatically calculates % wound closure by measuring the area of the wound and the area of cells migrating into the wound.
Machine Learning - Image Classification
Learns texture information from overall teacher images for judgment, and creates a decision tree for image classification. Can objectively classify cell images based on texture features that are difficult to evaluate with the human eye.
hPSC Colony Tracking
Automatically detects and identifies individual colonies of human pluripotent stem cells based on time-lapse phase-contrast images, and measures the area of the colony at each time point to generate growth curves.
* Scratch assay: An in vitro wound is created by scratching a confluent monolayer of cells. The wound is healed as cells migrate into and proliferate in the cleared area. The assay is often used as a measure of cell migration and proliferation.
Cell observation and cell state evaluation are often performed in the areas of drug discovery research and regenerative medicine, where cells are used as a model system. In addition, there is a general increase in demand for quantitative and objective analysis methods in cell-based studies.
Nikon’s Cell Evaluation technology can automatically capture and track various aspects of living cells in culture over time, including cell morphology, motility and proliferation. This capability stems from a unique combination of advanced technologies including non-invasive, long-term live cell imaging, which can visualize the functions and state changes in live cells, and powerful single cell tracking algorithms, which can track temporal changes in individual cells.
The four new analysis tools being released are Add-on Modules for Nikon’s CL-Quant image analysis software platform. These modules feature versatile and easy-to-use functions that support easier and more efficient cell evaluation.
Nikon aims to contribute to the acceleration of research into drug discovery and practical applications of regenerative medicine by providing a wide range of solutions that include software, hardware, and custom services that meet their users' challenges.
Features of Add-on Modules
The new Add-on Modules for the CL-Quant software provide a variety of analysis functions including cell counting, colony counting, and cell area percentage measurements, providing critical information for stable culture and manufacture of cells.
The Add-on Modules can be used as a protocol evaluation tool to create reproducibility indices for the development of culture processes, and to create cell quality indices for in-line inspection and shipping inspection during R&D phases where cells are cultured. These indices can be used to perform objective and uniform inspection during manufacturing. In drug discovery research, the Add-on Modules can be used to create efficient assays with live cells.
Machine Learning - Image Classification, one of the four types of Add-on Modules to be released, utilizes machine learning type AI technology. The module learns the feature values in entire teacher images and classifies cell images accordingly. It can identify cell forms by learning the judgment criteria of accomplished experts.