g-CXR-Net is a graphic interface to run CXR-Net two-module Artificial Intelligence pipeline for the quick detection of SARS-CoV-2 from Antero/Posterior (A/P) chest X-rays (CXRs).
The repository contains two folders, Module_1 and Module_2, required to build a functional CXR-Net model.
The GUI app, g_CXR_Net.py, can be launched from a virtual env with the command line syntax: python g_CXR_Net.py --xdir 'executable_dir', where 'executable_dir' is the directory where g_CXR_Net.py itself is located. Python scripts to generate icon links to run g-CXR-Net are in the directory CXR_Net_icons. The app can also be run outside a virtual environment, but in this case a full path to python location in the virtual env must be provided.
A video describing the use of g-CXR-Net can be watched/downloaded at http://veloce.med.wayne.edu/~gatti/neural-networks/cxr-net.html.
A brief medRxiv article describing the features of g-CXR-Net is available at https://medrxiv.org/cgi/content/short/2021.06.06.21258428v1, or by mobile device's via the QR code shown below:
For additional information e-mail to:
Domenico Gatti
Dept. Biochemistry, Microbiology, and Immunology, Wayne State University, Detroit, MI.
E-mail: dgatti@med.wayne.edu
website: http://veloce.med.wayne.edu/~gatti/