Computer vision is a field in artificial intelligence that aids computers to interpret and comprehend images. Machines can adequately recognize and classify objects using digital images from cameras and videos, as well as deep learning models, and then react to what they “see.”Researchers have recently developed algorithms for automatically analyzing biomedical videos captured by microscopy.
Researchers from Universidad Carlos III de Madrid (UC3M) have unveiled a technique to characterize and describe the behavior of the cells shown in the photographs. The UC3M engineering team’s novel techniques have been employed to measure living tissues. The findings demonstrate that neutrophils (a type of immune cell) exhibit diverse behaviors in the blood during inflammatory processes, with one of them triggered by the Fgr molecule being linked to the development of cardiovascular disease. Not just that, it has also led to the opinion that it may be possible to develop new medicines to reduce the severity of heart attacks.
The researchers’ method is a fully automated system based on computer vision techniques that allow scientists to define the cells under investigation by evaluating movies acquired by biologists using the intravital microscopy technique. Traditional biological experiments are usually supported by assessments of a few manually defined cells, whereas automatic evaluations of a few thousand cells’ morphologies, size, movement, and position compared to the blood vessel have been made. A complex biological analysis with more statistical significance might be undertaken in this approach.
A 5-minute video can be analyzed in only 15 minutes using the technology that has been developed. In terms of precision and time, it provides various advantages. Deep Neural Networks are used in the system. It is common knowledge that algorithms are essentially algorithms that adapt from instances. It’s also used in a new setting to provide enough examples for them to learn from. Engineers now use neural Networks for cell segmentation and detection.
Machine learning techniques, which are a discipline within Artificial Intelligence, include these networks (AI). Other statistical approaches and geometric models are also incorporated into the system.
The road ahead:
The system’s implementation software is adaptable, and the goal is to use it for different situations shortly. This work has already begun, and they are being used in various cases, such as researching the immunological behavior of T cells and dendritic cells in malignant tissues. It’s also worth noting that the preliminary findings are encouraging.
In any event, when conducting research in this subject, scholars emphasize the need to collaborate with a multidisciplinary team. Things will go more smoothly if scientists appreciate the importance of earlier communication between biologists, mathematicians, and engineers in understanding the fundamental principles of other fields before making real progress.