• Corpus ID: 232076291

CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rays

@article{Abdulah2021CXRNetAA,
  title={CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rays},
  author={Haikal Abdulah and Benjamin Huber and Sinan Lal and Hassan Abdallah and Luigi Leonardo Palese and Hamid Soltanian-Zadeh and Domenico L. Gatti},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.00087}
}
CXR-Net is a two-module Artificial Intelligence pipeline for the quick detection of SARS-CoV-2 from chest X-rays (CXRs). Module 1 was trained on a public dataset of 6395 CXRs with radiologist annotated lung contours to generate masks of the lungs that overlap the heart and large vasa. Module 2 is a hybrid convnet in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform (WST). Module 2 takes as… 
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2 Citations
Methods Citations
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2 Citations

A deep learning segmentation-classification pipeline for X-ray-based COVID-19 diagnosis
g-CXR-Net: A Graphic Application for the Rapid Recognition of SARS-CoV-2 from Chest X-Rays
g-CXR-Net is a graphic application for the rapid recognition of SARS-CoV-2 from Antero/Posterior chest X-rays. It employs the Artificial Intelligence engine of CXR-Net (arXiv:2103.00087) to generate…

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