Intensity Diffraction Tomography (IDT) is a new computational microscopy technique providing quantitative, volumetric, large field-of-view (FOV) phase imaging of biological samples. This approach uses computationally efficient inverse scattering models to recover 3D phase volumes of weakly scattering objects from intensity measurements taken under diverse illumination at a single focal plane. IDT is easily implemented in a standard microscope equipped with an LED array source and requires no exogenous contrast agents, making the technology widely accessible for biological research.Here, we discuss model and learning-based approaches for complex 3D object recovery with IDT. We present two model-based computational illumination strategies, multiplexed IDT (mIDT) [1] and annular IDT (aIDT) [2], that achieve high-throughput quantitative 3D object phase recovery at hardware-limited 4Hz and 10Hz volume rates, respectively. We illustrate these techniques on living epithelial buccal cells and Caenorhabditis elegans worms. For strong scattering object recovery with IDT, we present an uncertainty quantification framework for assessing the reliability of deep learning-based phase recovery methods [3]. This framework provides per-pixel evaluation of a neural network predictions confidence level, allowing for efficient and reliable complex object recovery. This uncertainty learning framework is widely applicable for reliable deep learning-based biomedical imaging techniques and shows significant potential for IDT.
Paper-Supported High-Throughput 3D Culturing, Trapping, and Monitoring of Caenorhabditis Elegans
We developed an innovative paper-based platform for high-throughput culturing, trapping, and monitoring of C. elegans. A 96-well array was readily fabricated by placing a nutrient-replenished paper substrate on a micromachined 96-well plastic frame, providing high-throughput 3D culturing environments and in situ analysis of the worms. The paper allows C. elegans to pass through the porous and aquatic paper matrix until the worms grow and reach the next developmental stages with the increased body size comparable to the paper pores. When the diameter of C. elegans becomes larger than the pore size of the paper substrate, the worms are trapped and immobilized for further high-throughput imaging and analysis. This work will offer a simple yet powerful technique for high-throughput sorting and monitoring of C. elegans at a different larval stage by controlling and choosing different pore sizes of paper. Furthermore, we developed another type of 3D culturing system by using paper-like transparent polycarbonate substrates for higher resolution imaging. The device used the multi-laminate structure of the polycarbonate layers as a scaffold to mimic the worm’s 3D natural habitats. Since the substrate is thin, mechanically strong, and largely porous, the layered structure allowed C. elegans to move and behave freely in 3D more »
- Award ID(s):
- 1703394
- Publication Date:
- NSF-PAR ID:
- 10190897
- Journal Name:
- Micromachines
- Volume:
- 11
- Issue:
- 1
- Page Range or eLocation-ID:
- 99
- ISSN:
- 2072-666X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- https://doi.org/10.3390/mi11010099
