11 citations · 13 across the 6 of their papers we have counts for
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eess.IV2022★ 11 cited
Multi-modal Brain Tumor Segmentation via Missing Modality Synthesis and Modality-level Attention Fusion
Ziqi Huang, Li Lin, Pujin Cheng +2
Multi-modal magnetic resonance (MR) imaging provides great potential for diagnosing and analyzing brain gliomas. In clinical scenarios, common MR sequences such as T1, T2 and FLAIR…
eess.IV2022★ 1 cited
Student Becomes Decathlon Master in Retinal Vessel Segmentation via Dual-teacher Multi-target Domain Adaptation
Linkai Peng, Li Lin, Pujin Cheng +2
Unsupervised domain adaptation has been proposed recently to tackle the so-called domain shift between training data and test data with different distributions. However, most of th…
eess.IV2022
Unsupervised Domain Adaptation for Cross-Modality Retinal Vessel Segmentation via Disentangling Representation Style Transfer and Collaborative Consistency Learning
Linkai Peng, Li Lin, Pujin Cheng +2
Various deep learning models have been developed to segment anatomical structures from medical images, but they typically have poor performance when tested on another target domain…