Semi-automatic liver tumor segmentation with adaptive region growing and graph cuts. - Zhen Yang; Yu-qian Zhao; Miao Liao; Shuan-hu Di; Ye-zhan Zeng (Biomed. Signal Process. Control., 2021)

Automatic liver tumor segmentation from CT images using hierarchical iterative superpixels and local statistical features. - Shuan-hu Di; Yuqian Zhao; Miao Liao; Zhen Yang; Ye-zhan Zeng (Expert Syst. Appl., 2022)

Single Image Dehazing Network Based on Serial Feature Attention. - Yan Lu; Miao Liao; Shuanhu Di; Yuqian Zhao (ICANN (3), 2023)

Pulmonary Nodule Detection from 3D CT Image with a Two-Stage Network. - Miao Liao; Zhiwei Chi; Huizhu Wu; Shuanhu Di; Yonghua Hu; Yunyi Li (Int. J. Intell. Syst., 2023)

TD-Net: A Hybrid End-to-End Network for Automatic Liver Tumor Segmentation From CT Images. - Shuan-hu Di; Yu-Qian Zhao; Miao Liao; Fan Zhang 106; Xiong Li 002 (IEEE J. Biomed. Health Informatics, 2023)

SPDFF-Net: Image Dehazing Network Based on Semantic Perception and Dual Feature Fusion. - Juanxiu Guo; Miao Liao; Shuanhu Di (CVDL, 2024)

FA-Net: A hierarchical feature fusion and interactive attention-based network for dose prediction in liver cancer patients. - Miao Liao; Shuanhu Di; Yuqian Zhao; Wei Liang 005; Zhen Yang (Artif. Intell. Medicine, 2024)

An Unsupervised Image Dehazing Method Using Patch-Line and Fuzzy Clustering-Line Priors. - Miao Liao; Yan Lu; Xiong Li 002; Shuanhu Di; Wei Liang 005; Victor Chang 001 (IEEE Trans. Fuzzy Syst., 2024)