Fusion of AI and optics for computational microscopy and sensing

Date: March 26, 2026
Time: 11:00 AM ET | 10:00 AM CT | 8:00 AM PT | 4:00 PM GMT
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In this webinar, Dr. Ozcan will provide an overview of recent work using deep neural networks to advance computational microscopy and sensing systems, as well as also cover their biomedical applications. He will discuss emerging opportunities to revolutionize tissue staining methods by digitally generating histological stains using trained deep neural networks to provide rapid, cost-effective, accurate, and environmentally friendly alternatives to standard chemical tissue staining methods. These deep learning-based virtual staining techniques can successfully generate different types of histological stains, including immunohistochemical stains, from label-free microscopic images of unstained samples by using autofluorescence microscopy, quantitative phase imaging, and reflectance confocal microscopy. His team also demonstrated similar approaches for transforming images of an already stained tissue sample into another type of stain to perform virtual stain-to-stain transformations. Finally, he will discuss work on paper-based sensors enabled by AI for multiplexed and cost-effective sensing of a panel of biomarkers within ~15 min using a mobile phone-based device.

