Author: Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Zhibing Lu; Stella K Kang; David Fenyo; Timothy Alcorn; Isaac P Dapkins; Iman Sharif; Deniz Vurmaz; Sayli S Modak; Kritika Srinivasan; Shruti Warhadpande; Ravi Shrivastav; John T McDevitt
Title: Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19 Document date: 2020_4_22
ID: h4lsvgxo_19
Snippet: Images were analyzed using a custom image analysis tool developed with MATLAB as described previously. 23 The fluorescence response of each bead was expressed as the average pixel intensity for a region of interest limited to the outer 10% of the bead diameter where the specific signal is concentrated. Bead sensors that were optically obstructed by debris or bubbles were excluded from analysis. Likewise, failed assay runs due to leaks were reject.....
Document: Images were analyzed using a custom image analysis tool developed with MATLAB as described previously. 23 The fluorescence response of each bead was expressed as the average pixel intensity for a region of interest limited to the outer 10% of the bead diameter where the specific signal is concentrated. Bead sensors that were optically obstructed by debris or bubbles were excluded from analysis. Likewise, failed assay runs due to leaks were rejected and reassayed. Curve fitting routines were processed in MATLAB® R2017b.
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