22
 OCT

22. October 2024

Live Cell Imaging in the Age of AI

Can you believe that there are around 30-40 trillion cells in the human body alone? Each has their own purpose and structure that help them to undertake their day-to-day tasks. With that many different cells in the body, can you imagine how many cells exist on our planet? Estimates are that there are around 10³². 

When analyzing individual cells, we need innovative technologies that can show us their structures, characteristics, and ongoing processes within the cells. One of these tools that can help us to investigate these cells is live cell imaging. 

Live cell imaging is a popular choice for capturing ongoing processes within cells without any delays, whereby it is essential that cells are maintained in conditions (e.g. temperature, CO₂ level) that help them to continue their normal processes. The market for live cell imaging is rapidly increasing - by 2032, this market should be worth $5.74 billion. Now, the market’s expansion is due to the amount of research that is needed to enhance live cell imaging technology. But there is also another factor for its increase: Artificial Intelligence (AI). 

Ultimately, incorporating AI into live cell imaging is extremely useful for learning more about cellular processes. AI tools can take the data and information that is captured from examining a cell and study and organize it.

Join us as we dive into more detail about AI and live cell imaging. In this article we will cover some benefits that AI has to offer to research relating to live cell imaging, to inform your decision.

Enhanced Detection and Analysis through Deep Learning

The cornerstone of AI's impact on live cell imaging is its ability to analyze complex data sets efficiently. 

Traditional methods of image analysis often fall short in handling the sheer volume and complexity of data generated by modern imaging techniques. However, AI, with a focus on deep learning algorithms, excels in extracting intricate features from images. This means it can improve the accuracy of cell and nuclei detection, classification, and segmentation.

This capability is instrumental in dissecting large-scale microscopic images, allowing for a granular understanding of cellular behavior and interactions within tissues.

Facilitating Precision Medicine

AI's role transcends the boundaries of image analysis, offering a conduit for integrating diverse data types. This integration is pivotal in the advancement of precision medicine, where the goal is to tailor therapeutic strategies to individual patient profiles. 

By combining live cell imaging with AI, researchers can unravel complex biological mechanisms at a cellular level, which can foster a holistic view of disease pathology. This synergy between AI and live cell imaging technologies accelerates the transition from basic research discoveries to clinical applications. Ultimately, it offers hope for personalized treatment modalities.

AI-powered tissue cytometers, like our own TissueFAXS series include multiple AI-tools and provide quantitative histopathological analysis. These systems offer detailed examinations of tissue and cellular structures, identifying changes brought about by diseases. Such tools are invaluable in elucidating the nuances of disease mechanisms and informing therapeutic decisions.

Revolutionizing Immunophenotyping

AI also plays a pivotal role in immunophenotyping. Immunophenotyping is the process of characterizing and identifying cell subtypes based on the presence of specific (surface) markers or antigens. This technique is fundamental in a variety of research domains, including oncology, pathology, immunology, and drug development.

By employing AI-supported image analysis in conjunction with automated whole slide imaging, platforms like TissueFAXS enable precise immunophenotyping while preserving tissue context. This dual capability is critical for understanding the spatial relationships and interactions of cellular phenotypes within tissues. As a result, it offers a comprehensive view of cellular microenvironment in the native tissue.

The integration of AI into live cell imaging heralds a new era in biomedical research. This is characterized by enhanced precision, depth, and efficiency in data analysis.

Through leveraging AI's computational prowess, scientists can navigate the complexities of cellular and tissue imaging, unlocking insights into disease pathology and potential therapeutic targets. This technological synergy not only accelerates scientific discovery but also paves the way for more personalized and effective healthcare solutions. 

Utilize AI as a Long-Term Solution for Live Cell Imaging

By focusing on nuclei segmentation and tissue classification, StrataQuest offers targeted, high-value applications of AI for spatial phenotyping. It steers clear of broader and unspecified functionalities.

This approach aligns with TissueGnostics’ strategy of delivering precise, reliable, and user-friendly tools for the scientific community. StrataQuest ensures that researchers can leverage the benefits of AI. Our software's capabilities are designed to meet the specific needs of spatial phenotyping.

Are You Ready to Utilize the Abilities of StrataQuest? 

One of the general benefits of AI is that it can improve the speed of analysis workflow as well as provide unbiased quantification of data. AI and live cell imaging go hand-in-hand to create the best results that are both reliable and accurate. As we progress towards the future, it is clear that we must focus on how we can enhance AI further for live cell imaging. This includes: 

• Combining AI-supported image analysis with other technologies, like spatial transcriptomics
• Utilizing the power of convolutional neural networks to provide the quick identification of the specific characteristics of the cells. 

The development of AI in live cell imaging is a fascinating topic. If you want to learn more about similar topics, why not look at our news page? 

We have a variety of articles available for you to browse through, including in relation to quantitative histopathology and tissue immunophenotyping. Have a look at our article about AI in Biomedicine where we invited researchers and experts to discuss the usability of AI in biomedical research and potential challenges associated with it.   

If you have any questions about AI or live cell imaging, please feel free to reach out to our specialists. Whether you are interested in time-lapse microscopy, fluorescent microscopy, confocal microscopes, or any other topics that are related to live cell imaging and AI, our experts will be here to help.