activity
20172024
most citedAn Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms

114 citations · 150 across the 16 of their papers we have counts for

collaborators
Showing eess.IVShow all

5 papers · 1 filter

eess.IV2022★ 1 cited

Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation

Zhenxi Zhang, Chunna Tian, Zhicheng Jiao

Semi-supervised learning methods have been explored in medical image segmentation tasks due to the scarcity of pixel-level annotation in the real scenario. Proto-type alignment bas…

eess.IV2020★ 7 cited

Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction

Zhenxi Zhang, Chunna Tian, Jie Li +3

Medical image segmentation is usually regarded as one of the most important intermediate steps in clinical situations and medical imaging research. Thus, accurately assessing the s…

eess.IV2019

Trident Segmentation CNN: A Spatiotemporal Transformation CNN for Punctate White Matter Lesions Segmentation in Preterm Neonates

Yalong Liu, Jie Li, Miaomiao Wang +3

Accurate segmentation of punctate white matter lesions (PWML) in preterm neonates by an automatic algorithm can better assist doctors in diagnosis. However, the existing algorithms…

eess.IV2019

Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants

Yalong Liu, Jie Li, Ying Wang +5

Accurate segmentation of punctate white matter lesion (PWML) in infantile brains by an automatic algorithm can reduce the potential risk of postnatal development. How to segment PW…

eess.IV2019★ 114 cited

An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms

Zhusi Zhong, Jie Li, Zhenxi Zhang +2

Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anat…