86 citations · 107 across the 7 of their papers we have counts for
7 papers
Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer
Yutong Xie, Dufan Wu, Bin Dong +1
We proved that a trained model in supervised deep learning minimizes the conditional risk for each input (Theorem 2.1). This property provided insights into the behavior of trained…
Development and Validation of a Deep Learning Model for Prediction of Severe Outcomes in Suspected COVID-19 Infection
Varun Buch, Aoxiao Zhong, Xiang Li +8
COVID-19 patient triaging with predictive outcome of the patients upon first present to emergency department (ED) is crucial for improving patient prognosis, as well as better hosp…
Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19
Aoxiao Zhong, Xiang Li, Dufan Wu +17
In recent years, deep learning-based image analysis methods have been widely applied in computer-aided detection, diagnosis and prognosis, and has shown its value during the public…
Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 Diagnosis
Young-Gon Kim, Kyungsang Kim, Dufan Wu +10
Purpose. Imaging plays an important role in assessing severity of COVID 19 pneumonia. However, semantic interpretation of chest radiography (CXR) findings does not include quantita…
Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks
Dufan Wu, Hui Ren, Quanzheng Li
Dynamic computed tomography perfusion (CTP) imaging is a promising approach for acute ischemic stroke diagnosis and evaluation. Hemodynamic parametric maps of cerebral parenchyma a…
Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
Dufan Wu, Kuang Gong, Kyungsang Kim +1
Deep neural networks have been proved efficient for medical image denoising. Current training methods require both noisy and clean images. However, clean images cannot be acquired…