FDCT: Fusion-Guided Dual-View Consistency Training for semi-supervised tissue segmentation on MRI

Zailiang Chen, Yazheng Hou, Hui Liu, Ziyu Ye, Rongchang Zhao, Hailan Shen

Abstract: Highlights•We propose a universal semi-supervised tissue segmentation framework on MRI called FDCT.•We improve the CBAM based on the task of this paper, which brings a boost to the network performance.•We propose the SBOM that generates boundary soft-label, which improves the quality of boundary segmentation.•Experiments on three datasets show that our method outperforms state-of-the-art semi-supervised medical image segmentation methods.