PA‐ResSeg: A phase attention residual network for liver tumor segmentation from multiphase CT images
Medical Physics2021Vol. 48(7), pp. 3752–3766
Citations Over TimeTop 10% of 2021 papers
Yingying Xu, Ming Cai, Lanfen Lin, Yue Zhang, Hongjie Hu, Zhiyi Peng, Qiaowei Zhang, Qingqing Chen, Xiongwei Mao, Yutaro Iwamoto, Xian‐Hua Han, Yen‐Wei Chen, Ruofeng Tong
Abstract
The study demonstrates that our method can effectively model information from multiphase CT images to segment liver tumors and outperforms other state-of-the-art methods. The PA-based MSF method can learn more representative multiphase features at multiple scales and thereby improve the segmentation performance. Besides, the proposed 3D BE-loss is conducive to tumor boundary segmentation by enforcing the network focus on boundary regions and marginal slices. Experimental results evaluated by quantitative metrics demonstrate the superiority of our PA-ResSeg over the best-known methods.