Life Sciences

Life sciences like other sciences heavily depend on routines such as counting, tracking, and classification. Today, many of these tasks can be successfully transferred to machine-learning and computer-vision systems. However, different studies and different objects either require adjustment of existing machine-learning models or tailor-developed solutions. BitRefine group offers tailor-made algorithms and is proud to take part in scientific research.

Cell counting

Studies conducted under the microscope are often related to cell counting and recording results in time. In major cases this is carried out manually, which is very time consuming. We offer a computer vision solution capable of recognizing shapes of individual cells and taking over all counting routines in a lab, saving time and reducing costs.

Cell classification

Another more sophisticated part of studying microscopic images is related to object classification. Working with cells or cell organelles, we first need to distinguish one type of object from another. Our research in this area relies on expertise in our other application in image recognition and the latest achievement in neural network solutions.

Fluorescence microscopic imaging

Currently, many laboratory methods use fluorescent stains to label molecules of interest. The resulting microscopic images differ a lot from standard images taken with use of visible light. Our research aims to build appropriate machine-learning models, capable of classifying, counting, and tracking fluorescent objects.

Our Vision

Today, a typical experiment requires a biologist to spend hours analyzing and annotating microscopic images. The increasing quantity of image data in cellular and molecular biology has begun to require advanced computer vision methods to take over at least primary image analysis routines. Modern deep-learning models already allow the identification of different types of cells or organelles, detection of anomalies, counting of those objects, or performing some other time-consuming tasks.

Of course, there is still a long way to go before scientists can undertake the use of intelligent computer vision systems to do fully automated measurements. However, we believe that current state-of-the-art solutions already can have a big impact in the area of life science by offering powerful tools to aid in biological research.

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