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11 March 2020 Computational illumination for high-throughput intensity diffraction tomography of dynamic biological samples (Conference Presentation)
Alex C. Matlock, Jiaji Li, Lei Tian
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Proceedings Volume 11249, Quantitative Phase Imaging VI; 112490A (2020) https://doi.org/10.1117/12.2545295
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
We present two computational illumination strategies for high-speed Intensity Diffraction Tomography (IDT) on dynamic, unlabeled biological samples. IDT provides quantitative volumetric reconstructions of biological samples but is slow, requiring hundreds of images under diverse illumination. We developed multiplexed IDT (mIDT) and annular IDT (aIDT) as software-based and hardware-based solutions improving IDT’s acquisition speed. mIDT optimally combines illuminations into each image for faster acquisition while aIDT uses fewer, single illuminations from a ring-geometry LED grid to achieve hardware-limited 5Hz and 10Hz volume rates, respectively. We demonstrate the improvement these techniques provide on living epithelial buccal cells and Caenorhabditis elegans worms.
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Alex C. Matlock, Jiaji Li, and Lei Tian "Computational illumination for high-throughput intensity diffraction tomography of dynamic biological samples (Conference Presentation)", Proc. SPIE 11249, Quantitative Phase Imaging VI, 112490A (11 March 2020); https://doi.org/10.1117/12.2545295
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KEYWORDS
Diffraction
Tomography
3D modeling
Image acquisition
Light emitting diodes
3D metrology
Inverse scattering
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