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Lung diseases classification in 2D using chest CT cases and Analysis the multi-channel effect on classification. This work is been done during summer internship July-Aguest 2018, Duke University Medical Center.
This Repo contains the updated implementation of our paper "Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features", Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131408 (16 March 2020)
Weakly supervised 3D classification of multi-disease chest CT scans using multi-resolution deep segmentation features via dual-stage CNN architecture (DenseVNet, 3D Residual U-Net).
The COVID-19 virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, so it’s important that you also practice respiratory etiquette (for example, by coughing into a flexed elbow). Deep learning can be used to detect COVID-19 in a patient as recent studies has shown that people suf…
Idiopathic pulmonary fibrosis (IPF) is a restrictive interstitial lung disease that causes lung function decline by lung tissue scarring. Although lung function decline is assessed by the forced vital capacity (FVC), determining the accurate progression of IPF remains a challenge. To address this challenge, we proposed Fibro-CoSANet, a novel end…
The objective of this project is to develop a model utilizing a convolutional neural network (CNN) for the classification of lung infections in individuals based on medical imagery.