1 citations · 1 across the 13 of their papers we have counts for
13 papers
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…
WSPolypNet: Weakly Supervised Polyp Localization in Colonoscopy Videos
Giseong Hwang, Minjae Jo, Yeonghyeon Park +9
Because dense frame-level annotation of colonoscopy videos is costly, we propose WSPolypNet, a weakly supervised framework for polyp localization using only video-level labels. WSP…
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…
LEXIC: Lightweight On-Device Decoding of Reading Comprehension from Eye Movements
Sumin Lee, Kyeonghun Kim, Subeen Lee +6
Predicting comprehension from eye movements could support adaptive reading interfaces. We present LEXIC, a compact recurrent model that predicts response correctness from fixation…
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…
NEMESIS: Noise-suppressed Efficient MAE with Enhanced Superpatch Integration Strategy
Kyeonghun Kim, Hyeonseok Jung, Youngung Han +9
Volumetric CT imaging is essential for clinical diagnosis, yet annotating 3D volumes is expensive and time-consuming, motivating self-supervised learning (SSL) from unlabeled data.…
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…
Autonomous Haiku Generation
Rui Aguiar, Kevin Liao
Artificial Intelligence is an excellent tool to improve efficiency and lower cost in many quantitative real world applications, but what if the task is not easily defined? What if…