Browsing by Author "Yang, Xi"

Now showing 1 - 4 of 4

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, Roarke
A 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.
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, Roarke
Noninvasive 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.
Open Access
Multi-View Weighted Network
(2016) Yang, Xi
Extensive investigation has been conducted on network data, especially weighted network in the form of symmetric matrices with discrete count entries. Motivated by statistical inference on multi-view weighted network structure, this paper proposes a Poisson-Gamma latent factor model, not only separating view-shared and view-specific spaces but also achieving reduced dimensionality. A multiplicative gamma process shrinkage prior is implemented to avoid over parameterization and efficient full conditional conjugate posterior for Gibbs sampling is accomplished. By the accommodating of view-shared and view-specific parameters, flexible adaptability is provided according to the extents of similarity across view-specific space. Accuracy and efficiency are tested by simulated experiment. An application on real soccer network data is also proposed to illustrate the model.
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, Roarke
This 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.