Pew-Thian Yap

Adjunct Professor of Computer Science

University of North Carolina at Chapel Hill

United States

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Pew-Thian Yap is an Adjunct Professor of Computer Science at The University of North Carolina at Chapel Hill, United States. His research areas focus on advanced imaging techniques and their applications in neuroscience, including MRI analysis, brain development, and machine learning in medical imaging. Recent publications include work on single-image super-resolution for infant brain MRI, functional development of the cerebellum, and methods for harmonizing structural MRI data.

Pew-Thian Yap

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Articles (20)

Unsupervised single-image super-resolution for infant brain MRI

Functional development of the human cerebellum from birth to age five

Disentangled latent energy-based style translation: An image-level structural MRI harmonization framework

Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection

TransFArchNet: Predicting dental arch curves based on facial point clouds in personalized panoramic X-ray imaging

Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI

Acceleration of Simultaneous Multislice Magnetic Resonance Fingerprinting With Spatiotemporal Convolutional Neural Network

Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI

Simulation-based inference of developmental EEG maturation with the spectral graph model

Learning multi-site harmonization of magnetic resonance images without traveling human phantoms

Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI

Longitudinal prediction of postnatal brain magnetic resonance images via a metamorphic generative adversarial network

A paired dataset of T1- and T2-weighted MRI at 3 Tesla and 7 Tesla

Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions

High-Resolution 3D Magnetic Resonance Fingerprinting With a Graph Convolutional Network

Multifaceted atlases of the human brain in its infancy

Dual Adversarial Attention Mechanism for Unsupervised Domain Adaptive Medical Image Segmentation

Special issue on machine learning and deep learning in magnetic resonance

Fast and Accurate Craniomaxillofacial Landmark Detection via 3D Faster R-CNN

Asymmetric multi-task attention network for prostate bed segmentation in computed tomography images

Collaborators (7)

Yoonmi Hong

Gang Li

Guoshi Li

Li Wang

Hongtu Zhu

Mingxia Liu

Andrea Bozoki

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