39 citations · 96 across the 4 of their papers we have counts for
4 papers
Weaving Attention U-net: A Novel Hybrid CNN and Attention-based Method for Organs-at-risk Segmentation in Head and Neck CT Images
Zhuangzhuang Zhang, Tianyu Zhao, Hiram Gay +2
In radiotherapy planning, manual contouring is labor-intensive and time-consuming. Accurate and robust automated segmentation models improve the efficiency and treatment outcome. W…
Pyramid Medical Transformer for Medical Image Segmentation
Zhuangzhuang Zhang, Weixiong Zhang
Deep neural networks have been a prevailing technique in the field of medical image processing. However, the most popular convolutional neural networks (CNNs) based methods for med…
ARPM-net: A novel CNN-based adversarial method with Markov Random Field enhancement for prostate and organs at risk segmentation in pelvic CT images
Zhuangzhuang Zhang, Tianyu Zhao, Hiram Gay +2
Purpose: The research is to develop a novel CNN-based adversarial deep learning method to improve and expedite the multi-organ semantic segmentation of CT images, and to generate a…
Semi-supervised Semantic Segmentation of Prostate and Organs-at-Risk on 3D Pelvic CT Images
Zhuangzhuang Zhang, Tianyu Zhao, Hiram Gay +2
Automated segmentation can assist radiotherapy treatment planning by saving manual contouring efforts and reducing intra-observer and inter-observer variations. The recent developm…