Fig. 4From: A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasetsBar charts of comparison results measured with DSC for eleven datasets grouped by different sampling strategies when training all datasets together by two-fold (the non-hybrid training schema fold 2 and fold 5 were used as baseline). The dataset-balance extent of sample strategy decreased from DOS > RSD > RS. Most datasets benefit from the hybrid training except the unbalanced dataset. LiTS and Porcine dataset was unbalanced dataset in DOS and RS strategy respectively. Zhujiang dataset cannot benefit from hybrid training in any sample strategyBack to article page