Paper 13329-91
Paper 13329-91
Computational label-free imaging of dry mass and orientation of organelles, cells, and tissues
27 January 2025 • 5:30 PM - 7:00 PM PST | Moscone West, Room 2003 (Level 2)
Abstract
The dry mass and the orientation of biomolecules are sensitive readouts of the architecture of organelles, cells, and tissues. These properties can be imaged without a label by measuring their permittivity tensor (PT), which describes how biomolecules affect the phase and polarization of light. Three-dimensional (3D) imaging of PT has been challenging. I'll discuss a recent label-free computational microscopy technique, PT imaging (PTI), for the 3D measurement of PT. PTI encodes the invisible PT into images using oblique illumination, polarization-sensitive detection, and volumetric sampling. PTI decodes the PT using an inverse algorithm based on an accurate vectorial image formation model. In this talk, I'll summarize forward models and strategies for reconstruction for robust 3D imaging at the spatial scales of organelles, cells, and tissues.
Presenter
Shalin B. Mehta
Chan Zuckerberg Biohub (United States)
Shalin Mehta developed signal processing algorithms for radars, before earning a Ph.D. in optics at the National University of Singapore from Colin Sheppard’s lab. His Ph.D. research led to elegant mathematical models and new label-free imaging technologies. He then worked at the intersection of technology development and quantitative biology at the Marine Biological Laboratory in Woods Hole as a Human Frontier Science Program (HFSP) Fellow. His postdoctoral research led to novel computational imaging methods to measure the molecular order of the cytoskeleton beyond the resolution limit. At CZ Biohub SF, Mehta leads the Computational Microscopy platform; he and his team integrate optics, inverse algorithms, and machine learning to build computational microscopy platforms that measure the biological architecture and activity with increasing accuracy, precision, and throughput.