Automatic lung segmentation in routine imaging is primarily a data diversity problem not a methodology problem

摘要

Schematic overview of the training and testing performed. We collected public datasets and two datasets from the routine. We used these datasets to train four generic semantic segmentation models and tested the trained models on public and routine data together with readily available lung segmentation systems