102 citations · 184 across the 12 of their papers we have counts for
14 papers
Multimodal Neurodegenerative Disease Subtyping Explained by ChatGPT
Diego Machado Reyes, Hanqing Chao, Juergen Hahn +2
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease; yet its currently available treatments are limited to stopping disease progression. Moreover, effectivenes…
Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation
Jiajin Zhang, Hanqing Chao, Amit Dhurandhar +4
Domain shift is a common problem in clinical applications, where the training images (source domain) and the test images (target domain) are under different distributions. Unsuperv…
When Neural Networks Fail to Generalize? A Model Sensitivity Perspective
Jiajin Zhang, Hanqing Chao, Amit Dhurandhar +4
Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions. This paper considers a more realistic yet more challenging scenari…
Regression Metric Loss: Learning a Semantic Representation Space for Medical Images
Hanqing Chao, Jiajin Zhang, Pingkun Yan
Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores. While training strategies and loss functions hav…
Cross-modal Attention for MRI and Ultrasound Volume Registration
Xinrui Song, Hengtao Guo, Xuanang Xu +6
Prostate cancer biopsy benefits from accurate fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images. In the past few years, convolutional neural networks (CNNs…
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
Nkechinyere N. Agu, Joy T. Wu, Hanqing Chao +5
Radiologists usually observe anatomical regions of chest X-ray images as well as the overall image before making a decision. However, most existing deep learning models only look a…
Task-Oriented Low-Dose CT Image Denoising
Jiajin Zhang, Hanqing Chao, Xuanang Xu +3
The extensive use of medical CT has raised a public concern over the radiation dose to the patient. Reducing the radiation dose leads to increased CT image noise and artifacts, whi…
GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set
Hanqing Chao, Kun Wang, Yiwei He +2
Gait is a unique biometric feature that can be recognized at a distance; thus, it has broad applications in crime prevention, forensic identification, and social security. To portr…
Robustified Domain Adaptation
Jiajin Zhang, Hanqing Chao, Pingkun Yan
Unsupervised domain adaptation (UDA) is widely used to transfer knowledge from a labeled source domain to an unlabeled target domain with different data distribution. While extensi…
Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography
Hanqing Chao, Hongming Shan, Fatemeh Homayounieh +7
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an op…
Integrative Analysis for COVID-19 Patient Outcome Prediction
Hanqing Chao, Xi Fang, Jiajin Zhang +13
While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome predictio…
Towards a Precipitation Bias Corrector against Noise and Maldistribution
Xiaoyang Xu, Yiqun Liu, Hanqing Chao +5
With broad applications in various public services like aviation management and urban disaster warning, numerical precipitation prediction plays a crucial role in weather forecast.…
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
Hanqing Chao, Yiwei He, Junping Zhang +1
As a unique biometric feature that can be recognized at a distance, gait has broad applications in crime prevention, forensic identification and social security. To portray a gait,…
Population Density-based Hospital Recommendation with Mobile LBS Big Data
Hanqing Chao, Yuan Cao, Junping Zhang +3
The difficulty of getting medical treatment is one of major livelihood issues in China. Since patients lack prior knowledge about the spatial distribution and the capacity of hospi…