5 citations · 9 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 5 cited
Enhancing Nucleus Segmentation with HARU-Net: A Hybrid Attention Based Residual U-Blocks Network
Junzhou Chen, Qian Huang, Yulin Chen +2
Nucleus image segmentation is a crucial step in the analysis, pathological diagnosis, and classification, which heavily relies on the quality of nucleus segmentation. However, the…
eess.IV2020★ 3 cited
Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation
Hao Tang, Xingwei Liu, Kun Han +6
Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achiev…
eess.IV2020★ 1 cited
AttentionAnatomy: A unified framework for whole-body organs at risk segmentation using multiple partially annotated datasets
Shanlin Sun, Yang Liu, Narisu Bai +5
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning. Recently, deep learning based methods for OAR delineation have…