6 papers
Anatomy-Privileged Distillation with Token Routing for MRI-Based Prediction of Perineural Invasion
Hyunsu Go, Youngung Han, Kyeonghun Kim +15
The paper introduces a teacher‑student deep learning framework that uses anatomy‑aware token routing to predict perineural invasion from T2‑weighted MRI without needing segmentatio…
SpikeDS: Dual Sparsity Spikformer for Perineural Invasion Prediction in 3D MRI
Induk Um, Youngung Han, Kyeonghun Kim +14
The paper introduces SpikeDS, a spiking neural network with dual sparsity mechanisms to efficiently predict perineural invasion in cholangiocarcinoma from 3D MRI scans, achieving h…
Adaptive Routing for Efficient Diffusion Transformer-Based PNI Prediction
Youngung Han, Dohyun Kweon, Kyeonghun Kim +15
The paper proposes a diffusion‑based transformer model with adaptive routing to predict perineural invasion in cholangiocarcinoma from MRI scans, achieving competitive accuracy whi…
MATHENA: Mamba-based Architectural Tooth Hierarchical Estimator and Holistic Evaluation Network for Anatomy
Kyeonghun Kim, Jaehyung Park, Youngung Han +17
Dental diagnosis from Orthopantomograms (OPGs) requires coordination of tooth detection, caries segmentation (CarSeg), anomaly detection (AD), and dental developmental staging (DDS…
FOSCU: Feasibility of Synthetic MRI Generation via Duo-Diffusion Models for Enhancement of 3D U-Nets in Hepatic Segmentation
Youngung Han, Kyeonghun Kim, Seoyoung Ju +8
Medical image segmentation faces fundamental challenges including restricted access, costly annotation, and data shortage to clinical datasets through Picture Archiving and Communi…
3D-LLDM: Label-Guided 3D Latent Diffusion Model for Improving High-Resolution Synthetic MR Imaging in Hepatic Structure Segmentation
Kyeonghun Kim, Jaehyeok Bae, Youngung Han +10
Deep learning and generative models are advancing rapidly, with synthetic data increasingly being integrated into training pipelines for downstream analysis tasks. However, in medi…