Deep Learning Lung Segmentation for mild, moderate and Severe ARDS lungs in computertomographic images
We programmed an artificial neural network based on the U-Net and trained with ~ 12000 CTs of the lungs. The trained model is able to segment the Lungs in the trained dataset to >95% fully automatically. The detection in the test set was ~ 85% accuracy. The intersection over union metric (Jacard Index) was used to determine the accuracy. Since 85% accuracy is not yet good enough, we of course continue to work on improving the modified U-Net and training with more different pathologies. (e.g. COVID-19 lungs, COPD, pneumonia, etc.)
For the whole process, we used NI LabVIEW version 2019, NI Vision version 2019 and the Deep Learning Toolkit for LabVIEW, DeepLTK version 4.01 from Ngene (Yerevan 0033, Armenia)