The dataset used has a large amount of variation in the angles the xrays were taken. This project presents a high resolution neural network to predict the presence of Covid-19 in chest xrays. The validation acuracy consistantly results in above 70% validation accuracy with some datasets presenting higher than 81.25% validation accuracy. The data used for training and validation can be found below. Dataset Trained with -> Joseph Paul Cohen and Paul Morrison and Lan Dao COVID-19 image data collection, arXiv:2003.11597, 2020 https://github.com/ieee8023/covid-chestxray-dataset @article{cohen2020covid, title={COVID-19 image data collection}, author={Joseph Paul Cohen and Paul Morrison and Lan Dao}, journal={arXiv 2003.11597}, url={https://github.com/ieee8023/covid-chestxray-dataset}, year={2020} }
-
Notifications
You must be signed in to change notification settings - Fork 1
The dataset used has a large amount of variation in the angles the xrays were taken. This project presents a high resolution neural network to predict the presence of Covid-19 in chest xrays.
License
lukerschwan/Covid-19_Lung_Image_CNN
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
The dataset used has a large amount of variation in the angles the xrays were taken. This project presents a high resolution neural network to predict the presence of Covid-19 in chest xrays.
Topics
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published