Browsing by Author "Kreiss, Lucas"
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Item Open Access Imaging dynamics beneath turbid media via parallelized single-photon detection(CoRR, 2021-07-03) Xu, Shiqi; Yang, Xi; Liu, Wenhui; Jonsson, Joakim; Qian, Ruobing; Konda, Pavan Chandra; Zhou, Kevin C; Kreiss, Lucas; Dai, Qionghai; Wang, Haoqian; Berrocal, Edouard; Horstmeyer, RoarkeNoninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task. While standard diffuse imaging methods measure optical absorption or fluorescent emission, it is also well-established that the temporal correlation of scattered coherent light diffuses through tissue much like optical intensity. Few works to date, however, have aimed to experimentally measure and process such temporal correlation data to demonstrate deep-tissue video reconstruction of decorrelation dynamics. In this work, we utilize a single-photon avalanche diode (SPAD) array camera to simultaneously monitor the temporal dynamics of speckle fluctuations at the single-photon level from 12 different phantom tissue surface locations delivered via a customized fiber bundle array. We then apply a deep neural network to convert the acquired single-photon measurements into video of scattering dynamics beneath rapidly decorrelating tissue phantoms. We demonstrate the ability to reconstruct images of transient (0.1-0.4s) dynamic events occurring up to 8 mm beneath a decorrelating tissue phantom with millimeter-scale resolution, and highlight how our model can flexibly extend to monitor flow speed within buried phantom vessels.Item Open Access Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second.(Nature photonics, 2023-05) Zhou, Kevin C; Harfouche, Mark; Cooke, Colin L; Park, Jaehee; Konda, Pavan C; Kreiss, Lucas; Kim, Kanghyun; Jönsson, Joakim; Doman, Thomas; Reamey, Paul; Saliu, Veton; Cook, Clare B; Zheng, Maxwell; Bechtel, John P; Bègue, Aurélien; McCarroll, Matthew; Bagwell, Jennifer; Horstmeyer, Gregor; Bagnat, Michel; Horstmeyer, RoarkeWide field of view microscopy that can resolve 3D information at high speed and spatial resolution is highly desirable for studying the behaviour of freely moving model organisms. However, it is challenging to design an optical instrument that optimises all these properties simultaneously. Existing techniques typically require the acquisition of sequential image snapshots to observe large areas or measure 3D information, thus compromising on speed and throughput. Here, we present 3D-RAPID, a computational microscope based on a synchronized array of 54 cameras that can capture high-speed 3D topographic videos over an area of 135 cm2, achieving up to 230 frames per second at spatiotemporal throughputs exceeding 5 gigapixels per second. 3D-RAPID employs a 3D reconstruction algorithm that, for each synchronized snapshot, fuses all 54 images into a composite that includes a co-registered 3D height map. The self-supervised 3D reconstruction algorithm trains a neural network to map raw photometric images to 3D topography using stereo overlap redundancy and ray-propagation physics as the only supervision mechanism. The resulting reconstruction process is thus robust to generalization errors and scales to arbitrarily long videos from arbitrarily sized camera arrays. We demonstrate the broad applicability of 3D-RAPID with collections of several freely behaving organisms, including ants, fruit flies, and zebrafish larvae.