57 citations · 101 across the 7 of their papers we have counts for
6 papers · 1 filter
Multi-hop Convolutions on Weighted Graphs
Qikui Zhu, Bo Du, Pingkun Yan
Graph Convolutional Networks (GCNs) have made significant advances in semi-supervised learning, especially for classification tasks. However, existing GCN based methods have two ma…
A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing
Zhao Peng, Xi Fang, Pingkun Yan +7
Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing orga…
Feature Fusion Encoder Decoder Network For Automatic Liver Lesion Segmentation
Xueying Chen, Rong Zhang, Pingkun Yan
Liver lesion segmentation is a difficult yet critical task for medical image analysis. Recently, deep learning based image segmentation methods have achieved promising performance,…
Deep Learning in Medical Image Registration: A Survey
Grant Haskins, Uwe Kruger, Pingkun Yan
The establishment of image correspondence through robust image registration is critical to many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitori…
Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation
Qikui Zhu, Bo Du, Pingkun Yan
Accurate segmentation of the prostate from magnetic resonance (MR) images provides useful information for prostate cancer diagnosis and treatment. However, automated prostate segme…
Knowledge-based Analysis for Mortality Prediction from CT Images
Hengtao Guo, Uwe Kruger, Ge Wang +2
Recent studies have highlighted the high correlation between cardiovascular diseases (CVD) and lung cancer, and both are associated with significant morbidity and mortality. Low-Do…