Rank Learning Based No-Reference Quality Assessment of Retargeted Images. - Lin Ma 002; Long Xu 001; Yichi Zhang 007; King Ngi Ngan; Yihua Yan (SMC, 2015)

No-Reference Retargeted Image Quality Assessment Based on Pairwise Rank Learning. - Lin Ma 002; Long Xu 001; Yichi Zhang 007; Yihua Yan; King Ngi Ngan (IEEE Trans. Multim., 2016)

Objective Quality Assessment of Image Retargeting by Incorporating Fidelity Measures and Inconsistency Detection. - Yichi Zhang 007; King Ngi Ngan; Lin Ma 002; Hongliang Li 001 (IEEE Trans. Image Process., 2017)

Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI. - Yichi Zhang 007 (M&Ms and EMIDEC/STACOM@MICCAI, 2020)

SAU-Net: Efficient 3D Spine MRI Segmentation Using Inter-Slice Attention. - Yichi Zhang 007; Lin Yuan; Yujia Wang; Jicong Zhang (MIDL, 2020)

Exploring Efficient Volumetric Medical Image Segmentation Using 2.5D Method: An Empirical Study. - Yichi Zhang 007; Qingcheng Liao; Jicong Zhang (CoRR, 2020)

Dual-Task Mutual Learning for Semi-supervised Medical Image Segmentation. - Yichi Zhang 007; Jicong Zhang (PRCV (3), 2021)

Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation. - Yichi Zhang 007; Qingcheng Liao; Rushi Jiao; Jicong Zhang (CoRR, 2021)

Exploiting Shared Knowledge From Non-COVID Lesions for Annotation-Efficient COVID-19 CT Lung Infection Segmentation. - Yichi Zhang 007; Qingcheng Liao; Lin Yuan; He Zhu; Jiezhen Xing; Jicong Zhang (IEEE J. Biomed. Health Informatics, 2021)

Bridging 2D and 3D segmentation networks for computation-efficient volumetric medical image segmentation: An empirical study of 2.5D solutions. - Yichi Zhang 007; Qingcheng Liao; Le Ding; Jicong Zhang (Comput. Medical Imaging Graph., 2022)

Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation. - Rushi Jiao; Yichi Zhang 007; Le Ding; Rong Cai; Jicong Zhang (CoRR, 2022)

Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge. - Alain Lalande; Zhihao Chen 005; Thibaut Pommier; Thomas Decourselle; Abdul Qayyum; Michel Salomon; Dominique Ginhac; Youssef Skandarani; Arnaud Boucher; Khawla Brahim; Marleen de Bruijne; Robin Camarasa; et al. (Medical Image Anal., 2022)

AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem? - Jun Ma 016; Yao Zhang 010; Song Gu; Cheng Zhu; Cheng Ge; Yichi Zhang 007; Xingle An; Congcong Wang; Qiyuan Wang; Xin Liu; Shucheng Cao; Qi Zhang 059; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Uncertainty-guided mutual consistency learning for semi-supervised medical image segmentation. - Yichi Zhang 007; Rushi Jiao; Qingcheng Liao; Dongyang Li; Jicong Zhang (Artif. Intell. Medicine, 2023)

How Segment Anything Model (SAM) Boost Medical Image Segmentation? - Yichi Zhang 007; Rushi Jiao (CoRR, 2023)

Segment anything model for medical image segmentation: Current applications and future directions. - Yichi Zhang 007; Zhenrong Shen 001; Rushi Jiao (Comput. Biol. Medicine, 2024)

Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation. - Rushi Jiao; Yichi Zhang 007; Le Ding; Bingsen Xue; Jicong Zhang; Rong Cai; Cheng Jin (Comput. Biol. Medicine, 2024)

NasalSeg Dataset for Nasal Cavity and Paranasal Sinuses Segmentation from CT Images. - Yichi Zhang 007; Jing Wang 198; Tan Pan; Quanlin Jiang; Jingjie Ge; Xin Guo; Chen Jiang; Jie Lu; Jianning Zhang; Xueling Liu; Mei Tian; Yuan Qi; et al. (Zenodo, 2024)

NasalSeg Dataset for Nasal Cavity and Paranasal Sinuses Segmentation from CT Images. - Yichi Zhang 007; Jing Wang 198; Tan Pan; Quanlin Jiang; Jingjie Ge; Xin Guo; Chen Jiang; Jie Lu; Jianning Zhang; Xueling Liu; Mei Tian; Yuan Qi; et al. (Zenodo, 2024)

SemiSAM+: Rethinking semi-supervised medical image segmentation in the era of foundation models. - Yichi Zhang 007; Bohao Lv; Le Xue; Wenbo Zhang; Yuchen Liu; Yu Fu; Yuan Cheng; Yuan Qi (Medical Image Anal., 2025)