A multi-objective segmentation method for chest X-rays based on collaborative learning from multiple partially annotated datasets

Hongyu Wang, Dandan Zhang, Jun Feng, Lucia Cascone, Michele Nappi, Shaohua Wan

Abstract: Highlights•This is the multi-organ segmentation framework for chest X-rays.•It stands out by collaborative learning on multiple partially annotated datasets.•We construct a shared encoder using densely connected blocks.•It incorporates a synergistic attention skip connection module and an attention-guided multi-scale feature selection module.•An attention oriented dual decoder structure addresses the challenge of low segmentation accuracy.