30 citations · 33 across the 2 of their papers we have counts for
4 papers
A novel adversarial learning strategy for medical image classification
Zong Fan, Xiaohui Zhang, Jacob A. Gasienica +7
Deep learning (DL) techniques have been extensively utilized for medical image classification. Most DL-based classification networks are generally structured hierarchically and opt…
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…
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…