All-Virtual OSA Biophotonics Congress Introduces Solutions to Challenges in Biomedical Research
Suzanne Ffolkes, OSA Chief Communications Officer
The OSA Biophotonics Congress: Optics in the Life Sciences held 12 – 16 April 2021, featured presentations on technologies transforming biomedical imaging, clinical investigations and more. Over 460 registrants from 37 countries participated in talks highlighting the role of optics in making instrumentation and relevant tools available to biological researchers, clinicians, surgeons and physicians. Poster sessions and a virtual exhibit also demonstrated the breadth of research and commercial applications.
The technical content showcased advances in machine learning, one of the major themes of the virtual event, which is being used for many applications. Enhancing resolution, reducing noise, improving cell identification and adding false stains to an otherwise un-stained histology image are among the ways in which this technology is being applied.
“This congress continues to draw experts for thoughtful, informative discussions around the use of optical technologies in biological and medical research,” said Peter So, 2021 OSA Biophotonics Congress Chair. “We encourage registrants to access the recorded content to learn more about the exciting techniques addressing challenges in the field.”
In her talk titled “Computational 3D Fluorescence Microscopy,” Laura Waller of University of California, Berkeley, USA described a compact and inexpensive microscope with extraordinary capabilities. The instrument uses computational imaging techniques to enable a single measurement for generating enough information to make a complete 3D image.
Molly May with the Institute of Biomedical Physics, USA discussed wavefront correction in her talk “Fast Holographic Scattering Compensation for Deep Tissue Biological Imaging.” The technique works faster than other current approaches to overcome some of the heavy scattering in tissue. Scattering severely limits the depth that can be achieved by two-photon and other types of optical imaging.
Using Generative Adversarial Networks (GANs) in biomedical optics was the focus of a deep learning presentation. Taylor Bobrow of Johns Hopkins University, USA talked about using GANs and deep learning techniques with artificially constructed image data that incorporate the characteristics being targeted. The machine learning algorithms can remove speckle noise and produce realistic images.
A general noise reduction technique demonstrated the effective use of machine learning in a presentation by Jerome Lecoq of Stanford University, USA. In his talk titled “The Death of Shot Noise: Removing Uncorrelated Noise in Systems Neuroscience Using Deep Interpolation,” he described using a machine learning technique to substantially reduce the random noise from microscope images. Even though the initial training was done with a very large and specific image database (over 10^5 images), the technique could be used successfully with other types of images using far fewer images in the training set.
The three plenary speakers discussed advances in alternative strategies for 3D imaging, quantum enhanced superresolution confocal microscopy and petascale microscopy for brain mapping -- Sandrine Lévêque-Fort, CNRS Researcher Director at the Institute of Molecular Science, Paris Saclay University, France; Dan Oron, Professor, Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, Israel and R. Clay Reid, Senior Investigator, Allen Institute for Brain Science, USA.
Registrants can access presentation recordings on the Biophotonics Congress schedule for up to 60 days.