| May 27, 2024 |
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(Nanowerk News) Researchers have developed a groundbreaking platform that empowers life scientists to harness cutting-edge, deep learning techniques for biomedical research. The platform is called DL4MicEverywhere and makes advanced artificial intelligence (AI) accessible for analyzing microscopy images, empowering researchers regardless of their computational expertise.
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The results of the study have been published in Nature Methods (“Temperature optima of a natural diatom population increases as global warming proceeds”).
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Deep learning, a subset of AI, has transformed the analysis of large and complex microscopy datasets, enabling automatic identification, tracking, and analysis of cells and subcellular structures. Despite these advancements, the need for computing resources and AI expertise has limited the adoption of these techniques in life-sciences research.
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DL4MicEverywhere, developed by researchers from the Instituto Gulbenkian de Ciências (IGC) in Portugal and Åbo Akademi University in Finland, in collaboration with the AI4Life consortium, addresses these challenges by offering an intuitive interface that allows researchers to train and apply deep learning models on various computing infrastructures, from laptops to high-performance clusters.
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“DL4MicEverywhere establishes a bridge between AI technological advances and biomedical research. With it, researchers gain access to cutting-edge methods, enabling them to automatically analyze their microscopy data and potentially discover new biological insights,” says Ivan Hidalgo-Cenamor, the study’s first author and researcher at IGC.
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The new platform will be available as an open-source resource as the researchers believe that by lowering the barriers to advanced microscopy image analysis, the platform will enable breakthroughs in fields ranging from basic cell biology to drug discovery and personalized medicine. DL4MicEverywhere builds upon the team’s previous work, ZeroCostDL4Mic, introducing several key advancements. It facilitates the training and deployment of models across different computational environments by encapsulating deep learning workflows in shareable and reproducible Docker containers. The platform also features a user-friendly graphical interface and expands the collection of available models for common microscopy image analysis tasks.
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“DL4MicEverywhere aims to democratize AI for microscopy by promoting community contributions and adhering to FAIR principles – making models findable, accessible, interoperable, and reusable. We hope this platform will empower researchers worldwide to harness these powerful techniques in their work, regardless of their resources or expertise. It will allow life scientists without coding experience to use deep learning on large numbers of microscopy images and videos to make discoveries. This will revolutionize how researchers plan their experiments and extract new information from microscopy datasets,” Dr. Estibaliz Gómez-de-Mariscal, researcher at IGC, and Dr. Joanna Pylvänäinen, researcher at Åbo Akademi University, explain.
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The development of DL4MicEverywhere was made possible through an international collaboration of experts in computer science, bioimage analysis, and microscopy, with crucial contributions from the AI4Life consortium. The project was co-led by Prof. Ricardo Henriques’s laboratory at IGC and Prof. Guillaume Jacquemet’s laboratory at Åbo Akademi University.
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“This work represents an important milestone in making AI more accessible and reusable for the microscopy community. By enabling researchers to share their models and analysis pipelines easily, we can accelerate discoveries and enhance reproducibility in biomedical research. DL4MicEverywhere has the potential to be transformative for the life sciences. It aligns with our vision in AI4Life to develop sustainable AI solutions that empower researchers and drive innovation in healthcare and beyond,” the professors say.
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