Browsing by Author "Xu, Shiqi"
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Item Open Access A multiple instance learning approach for detecting COVID-19 in peripheral blood smears.(PLOS digital health, 2022-08) Cooke, Colin L; Kim, Kanghyun; Xu, Shiqi; Chaware, Amey; Yao, Xing; Yang, Xi; Neff, Jadee; Pittman, Patricia; McCall, Chad; Glass, Carolyn; Jiang, Xiaoyin Sara; Horstmeyer, RoarkeA wide variety of diseases are commonly diagnosed via the visual examination of cell morphology within a peripheral blood smear. For certain diseases, such as COVID-19, morphological impact across the multitude of blood cell types is still poorly understood. In this paper, we present a multiple instance learning-based approach to aggregate high-resolution morphological information across many blood cells and cell types to automatically diagnose disease at a per-patient level. We integrated image and diagnostic information from across 236 patients to demonstrate not only that there is a significant link between blood and a patient's COVID-19 infection status, but also that novel machine learning approaches offer a powerful and scalable means to analyze peripheral blood smears. Our results both backup and enhance hematological findings relating blood cell morphology to COVID-19, and offer a high diagnostic efficacy; with a 79% accuracy and a ROC-AUC of 0.90.Item Open Access Computational Bio-Optical Imaging with Novel Sensor Arrays(2023) Xu, ShiqiOptical imaging is an essential tool for studying life sciences. Existing biomedical optical systems range from microscopes in clinics that use wave optics principles to examine pathological samples at high resolution, to photoplethysmography in everyday smartwatches utilizing diffuse optics technologies for monitoring deep tissue physiology. An optical system, such as a photography solution in a studio, typically consists of three parts: illumination, objects of interest, and recording devices. Over the past decades, thanks to rapid advancements in semiconductor manufacturing, numerous new and exciting optical devices have emerged. These include low-cost, small form-factor LEDs and CMOS camera sensors in budget tablet devices, as well as high-density time-of-flight array detectors in recent generations of iPhones, for example. Moore's Law, on the other hand, has driven significant development in powerful yet inexpensive computational tools. As a result, nowadays, analogous to other medical imaging modalities such as X-ray CT and MRI, multiplexed optical measurements that may not resemble the object of interest can be recorded and post-processed to reconstruct useful images for human perception. In this thesis, several new computational optical imaging techniques at different scales will be discussed. These range from vectorial tomographic microscopies for imaging anisotropic cells and tissue, to high-throughput imaging systems capable of recording eukaryotic colonies at mesoscopic scales, and novel single-photon-sensitive sensing methods for non-invasive imaging of macroscopic transient dynamics deep within turbid volumes.
Item Open Access Gigapixel imaging with a novel multi-camera array microscope.(eLife, 2022-12) Thomson, Eric E; Harfouche, Mark; Kim, Kanghyun; Konda, Pavan C; Seitz, Catherine W; Cooke, Colin; Xu, Shiqi; Jacobs, Whitney S; Blazing, Robin; Chen, Yang; Sharma, Sunanda; Dunn, Timothy W; Park, Jaehee; Horstmeyer, Roarke W; Naumann, Eva AThe dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. Further, the MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms across a wide range of spatial scales.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 Quantitative Jones matrix imaging using vectorial Fourier ptychography(2021-09-30) Dai, Xiang; Xu, Shiqi; Yang, Xi; Zhou, Kevin C; Glass, Carolyn; Konda, Pavan Chandra; Horstmeyer, RoarkeThis paper presents a microscopic imaging technique that uses variable-angle illumination to recover the complex polarimetric properties of a specimen at high resolution and over a large field-of-view. The approach extends Fourier ptychography, which is a synthetic aperture-based imaging approach to improve resolution with phaseless measurements, to additionally account for the vectorial nature of light. After images are acquired using a standard microscope outfitted with an LED illumination array and two polarizers, our vectorial Fourier Ptychography (vFP) algorithm solves for the complex 2x2 Jones matrix of the anisotropic specimen of interest at each resolved spatial location. We introduce a new sequential Gauss-Newton-based solver that additionally jointly estimates and removes polarization-dependent imaging system aberrations. We demonstrate effective vFP performance by generating large-area (29 mm$^2$), high-resolution (1.24 $\mu$m full-pitch) reconstructions of sample absorption, phase, orientation, diattenuation, and retardance for a variety of calibration samples and biological specimens.