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Im, Hyungsoon

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Hyungsoon

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Im, Hyungsoon
Author's Publications: search.filters.isAuthorOfPublication.032b46b6-3984-4577-8573-5525156c3443

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    Holographic Assessment of Lymphoma Tissue (HALT) for Global Oncology Field Applications
    (Ivyspring International Publisher, 2016) Pathania, Divya; Im, Hyungsoon; Kilcoyne, Aoife; Sohani, Aliyah R.; Fexon, Lioubov; Pivovarov, Misha; Abramson, Jeremy; Randall, Thomas; Chabner, Bruce; Weissleder, Ralph; Lee, Hakho; Castro, Cesar
    Low-cost, rapid and accurate detection technologies are key requisites to cope with the growing global cancer challenges. The need is particularly pronounced in resource-limited settings where treatment opportunities are often missed due to the absence of timely diagnoses. We herein describe a Holographic Assessment of Lymphoma Tissue (HALT) system that adopts a smartphone as the basis for molecular cancer diagnostics. The system detects malignant lymphoma cells labeled with marker-specific microbeads that produce unique holographic signatures. Importantly, we optimized HALT to detect lymphomas in fine-needle aspirates from superficial lymph nodes, procedures that align with the minimally invasive biopsy needs of resource-constrained regions. We equipped the platform to directly address the practical needs of employing novel technologies for “real world” use. The HALT assay generated readouts in <1.5 h and demonstrated good agreement with standard cytology and surgical pathology.
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    Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography
    (Nature Publishing Group, 2016) Song, Jun; Leon Swisher, Christine; Im, Hyungsoon; Jeong, Sangmoo; Pathania, Divya; Iwamoto, Yoshiko; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho
    Lens-free digital in-line holography (LDIH) is a promising technology for portable, wide field-of-view imaging. Its resolution, however, is limited by the inherent pixel size of an imaging device. Here we present a new computational approach to achieve sub-pixel resolution for LDIH. The developed method is a sparsity-based reconstruction with the capability to handle the non-linear nature of LDIH. We systematically characterized the algorithm through simulation and LDIH imaging studies. The method achieved the spatial resolution down to one-third of the pixel size, while requiring only single-frame imaging without any hardware modifications. This new approach can be used as a general framework to enhance the resolution in nonlinear holographic systems.