57 citations · 101 across the 5 of their papers we have counts for
14 papers
Noise Entangled GAN For Low-Dose CT Simulation
Chuang Niu, Ge Wang, Pingkun Yan +8
We propose a Noise Entangled GAN (NE-GAN) for simulating low-dose computed tomography (CT) images from a higher dose CT image. First, we present two schemes to generate a clean CT…
Decreasing the Surgical Errors by Neurostimulation of Primary Motor Cortex and the Associated Brain Activation via Neuroimaging
Yuanyuan Gao, Lora Cavuoto, Anirban Dutta +9
Acquisition of fine motor skills is a time-consuming process as it requires frequent repetitions. Transcranial electrical stimulation is a promising means of enhancing simple motor…
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…