output
20182025
most citedIterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation

45 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

5 papers

cs.CV2025★ 1 cited

Unsupervised Anomaly Detection in Brain MRI via Disentangled Anatomy Learning

Tao Yang, Xiuying Wang, Hao Liu +4

Detection of various lesions in brain MRI is clinically critical, but challenging due to the diversity of lesions and variability in imaging conditions. Current unsupervised learni…

cs.CV2025★ 45 cited

Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation

Qiangguo Jin, Hui Cui, Junbo Wang +7

Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-l…

eess.IV2020★ 32 cited

COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19

Guoqing Bao, Huai Chen, Tongliang Liu +4

There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis me…

cs.CV2019★ 13 cited

Shape-Aware Organ Segmentation by Predicting Signed Distance Maps

Yuan Xue, Hui Tang, Zhi Qiao +6

In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall sha…

cs.CV2018★ 4 cited

MMFNet: A Multi-modality MRI Fusion Network for Segmentation of Nasopharyngeal Carcinoma

Huai Chen, Yuxiao Qi, Yong Yin +5

Segmentation of nasopharyngeal carcinoma (NPC) from Magnetic Resonance Images (MRI) is a crucial prerequisite for NPC radiotherapy. However, manually segmenting of NPC is time-cons…