Ken Chang

Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results

Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence

Fair Conformal Predictors for Applications in Medical Imaging

How Machine Learning is Powering Neuroimaging to Improve Brain Health

Federated Learning for Multicenter Collaboration in Ophthalmology

Federated Learning for Multicenter Collaboration in Ophthalmology

Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma

Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI

Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning

AnatomiCuts: Hierarchical clustering of tractography streamlines based on anatomical similarity

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas

Epidermal devices for noninvasive, precise, and continuous mapping of macrovascular and microvascular blood flow