14 papers · 1 filter
Order-Aware 2.5D Multiple Instance Learning for Preoperative MRI-Based Perineural Invasion Risk Assessment in Intrahepatic Cholangiocarcinoma
Hyunsu Go, Youngung Han, Kyeonghun Kim +11
Perineural invasion (PNI) is an adverse histopathologic marker in intrahepatic cholangiocarcinoma (ICC), but it is usually confirmed only after resection. Preoperative T2-weighted…
SCINTILLA-SNN: A Spiking Multi-Scale Selective Aggregation Network for Perineural Invasion Prediction
Youngung Han, Yului Jeong, Kyeonghun Kim +11
Preoperative prediction of perineural invasion (PNI) in cholangiocarcinoma (CCA) is clinically valuable but remains challenging because PNI-related cues on magnetic resonance imagi…
Anatomy-Privileged Distillation with Token Routing for MRI-Based Prediction of Perineural Invasion
Hyunsu Go, Youngung Han, Kyeonghun Kim +15
Perineural invasion (PNI) is associated with poor postoperative outcomes in intrahepatic cholangiocarcinoma, but it is confirmed by surgical pathology. Existing preoperative imagin…
SpikeDS: Dual Sparsity Spikformer for Perineural Invasion Prediction in 3D MRI
Induk Um, Youngung Han, Kyeonghun Kim +14
Perineural invasion (PNI) is associated with poor prognosis in cholangiocarcinoma (CCA). However, its detection from 3D MRI remains challenging due to the subtle and spatially hete…
Adaptive Routing for Efficient Diffusion Transformer-Based PNI Prediction
Youngung Han, Dohyun Kweon, Kyeonghun Kim +15
Perineural invasion (PNI) is a critical prognostic factor in cholangiocarcinoma. However, its preoperative prediction from magnetic resonance imaging (MRI) remains challenging due…
LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI
Youngung Han, Hyunsu Go, Kyeonghun Kim +9
Perineural invasion (PNI) is a clinically relevant indicator of tumor aggressiveness and can influence surgical decision-making, motivating interest in reliable preoperative assess…
MMA-Former: Multi-Window Mixture-of-Head Attention Transformer for Adaptive PNI Prediction in 3D MRI
Youngung Han, Induk Um, Kyeonghun Kim +9
Perineural invasion (PNI) is a critical prognostic factor in cholangiocarcinoma. Non-invasive prediction from 3D MRI is challenging, demanding models that efficiently capture both…
ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification
Anna Jung, Kyeonghun Kim, Youngung Han +6
Whole slide images (WSIs) provide rich diagnostic information for computational pathology, but their gigapixel scale, stain variation, scanner differences, tissue artifacts, and li…
COTTA: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving
Seohyoung Park, Jaeyeol Lim, Seoyoung Ju +3
Developing robust models to accurately predict the trajectories of surrounding agents is fundamental to autonomous driving safety. However, most public datasets, such as the Waymo…
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…
MAESIL: Masked Autoencoder for Enhanced Self-supervised Medical Image Learning
Kyeonghun Kim, Hyeonseok Jung, Youngung Han +14
Training deep learning models for three-dimensional (3D) medical imaging, such as Computed Tomography (CT), is fundamentally challenged by the scarcity of labeled data. While pre-t…
NeoNet: An End-to-End 3D MRI-Based Deep Learning Framework for Non-Invasive Prediction of Perineural Invasion via Generation-Driven Classification
Youngung Han, Minkyung Cha, Kyeonghun Kim +12
Minimizing invasive diagnostic procedures to reduce the risk of patient injury and infection is a central goal in medical imaging. And yet, noninvasive diagnosis of perineural inva…
CIPHER: Counterfeit Image Pattern High-level Examination via Representation
Kyeonghun Kim, Youngung Han, Seoyoung Ju +9
The rapid progress of generative adversarial networks (GANs) and diffusion models has enabled the creation of synthetic faces that are increasingly difficult to distinguish from re…
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…