Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Images

@article{Wong2021FibrosisNetAT,
  title={Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Images},
  author={Alexander Wong and Jack Lu and Adam L Dorfman and Paul McInnis and Mahmoud Famouri and Daniel Manary and James Ren Hou Lee and Michael Lynch},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.04008}
}
Pulmonary fibrosis is a devastating chronic lung disease that causes irreparable lung tissue scarring and damage, resulting in progressive loss in lung capacity and has no known cure. A critical step in the treatment and management of pulmonary fibrosis is the assessment of lung function decline, with computed tomography (CT) imaging being a particularly effective method for determining the extent of lung damage caused by pulmonary fibrosis. Motivated by this, we introduce Fibrosis-Net, a deep… Expand

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