128 citations · 319 across the 15 of their papers we have counts for
16 papers
Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models
Haoyue Zhang, Jennifer S. Polson, Eric J. Yang +3
For acute ischemic stroke (AIS) patients with large vessel occlusions, clinicians must decide if the benefit of mechanical thrombectomy (MTB) outweighs the risks and potential comp…
RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans
Pengxin Yu, Haoyue Zhang, Han Kang +3
In clinical practice, anisotropic volumetric medical images with low through-plane resolution are commonly used due to short acquisition time and lower storage cost. Nevertheless,…
Transformer Lesion Tracker
Wen Tang, Han Kang, Haoyue Zhang +3
Evaluating lesion progression and treatment response via longitudinal lesion tracking plays a critical role in clinical practice. Automated approaches for this task are motivated b…
Federated Learning with Research Prototypes for Multi-Center MRI-based Detection of Prostate Cancer with Diverse Histopathology
Abhejit Rajagopal, Ekaterina Redekop, Anil Kemisetti +5
Early prostate cancer detection and staging from MRI are extremely challenging tasks for both radiologists and deep learning algorithms, but the potential to learn from large and d…
Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
Kexin Ding, Mu Zhou, Zichen Wang +4
Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales. The development…
Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets
Chao Chen, Catalina Raymond, Bill Speier +5
\textit{Objective:} Gadolinium-based contrast agents (GBCAs) have been widely used to better visualize disease in brain magnetic resonance imaging (MRI). However, gadolinium deposi…