Label-Free Detection of Human Coronaviruses in Infected Cells Using Enhanced Darkfield Hyperspectral Microscopy (EDHM)

Abstract

Human coronaviruses (HCoV) are causative agents of mild to severe intestinal and respiratory infections in humans. In the last 15 years, we have witnessed the emergence of three zoonotic, highly pathogenic HCoVs. Thus, early and accurate detection of these viral pathogens is essential for preventing transmission and providing timely treatment and monitoring of drug resistance. Herein, we applied enhanced darkfield hyperspectral microscopy (EDHM), a novel non-invasive, label-free diagnostic tool, to rapidly and accurately identify two strains of HCoVs, i.e., OC43 and 229E. The EDHM technology allows collecting the optical image with spectral and spatial details in a single measurement without direct contact between the specimen and the sensor. Thus, it can directly map spectral signatures specific for a given viral strain in a complex biological milieu. Our study demonstrated distinct spectral patterns for HCoV-OC43 and HCoV-229E virions in the solution, serving as distinguishable parameters for their differentiation. Furthermore, spectral signatures obtained for both HCoV strains in the infected cells displayed a considerable peak wavelength shift compared to the uninfected cell, indicating that the EDHM is applicable to detect HCoV infection in mammalian cells.

Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs

“…Object detection is a fundamental problem in computer vision that simultaneously classifies and localizes all objects in images or videos [ 1 , 2 , 3 ]. With the fast development of deep learning, object detection has achieved great success and been applied to many real-world tasks such as object tracking [ 4 , 5 ], image classification [ 6 , 7 , 8 ], segmentation [ 9 , 10 ], self-driving [ 11 ], and medical image analysis [ 12 , 13 ]. Generally speaking, the detection models could be categorized as two-stage detectors and one-stage detectors.…”