91 citations · 236 across the 31 of their papers we have counts for
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IdenBAT: Disentangled Representation Learning for Identity-Preserved Brain Age Transformation
Junyeong Maeng, Kwanseok Oh, Wonsik Jung +1
Brain age transformation aims to convert reference brain images into synthesized images that accurately reflect the age-specific features of a target age group. The primary objecti…
DyMix: Dynamic Frequency Mixup Scheduler based Unsupervised Domain Adaptation for Enhancing Alzheimer's Disease Identification
Yooseung Shin, Kwanseok Oh, Heung-Il Suk
Advances in deep learning (DL)-based models for brain image analysis have significantly enhanced the accuracy of Alzheimer's disease (AD) diagnosis, allowing for more timely interv…
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation
Kwanseok Oh, Eunjin Jeon, Da-Woon Heo +2
Single-source domain generalization (SDG) in medical image segmentation (MIS) aims to generalize a model using data from only one source domain to segment data from an unseen targe…
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
Kwanseok Oh, Jieun Lee, Da-Woon Heo +2
Ultrahigh-field (UHF) magnetic resonance imaging (MRI), i.e., 7T MRI, provides superior anatomical details of internal brain structures owing to its enhanced signal-to-noise ratio…