7 papers
ENC-ODE: Event-level Neurodegenerative Modeling in Continuous Time with Neural ODEs
Yujee Song, Seunghun Baek, Guorong Wu +1
Accurately predicting the temporal evolution of clinical biomarkers is crucial for the early diagnosis and management of neurodegenerative diseases such as Alzheimer's disease. How…
Set-Inclusive Uncertainty Modeling for Robust Brain Tumor Segmentation
Seunghun Baek, Jihwan Park, Jaeyoon Sim +3
Multimodal MRI is essential for accurate brain tumor segmentation. However, acquiring all modalities at inference is often challenging in practice, which causes intrinsic uncertain…
Multi-Modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification
Jaeyoon Sim, Minjae Lee, Guorong Wu +1
The graphical representation of the brain offers critical insights into diagnosing and prognosing neurodegenerative disease via relationships between regions of interest (ROIs). De…
Learning Multi-Scale Hypergraph for High-Order Brain Connectivity Analysis
Jaeyoon Sim, Soojin Hwang, Seunghun Baek +2
Understanding complex interactions between brain regions is critical for early neurodegenerative disease classification such as Alzheimer's Disease (AD) and Parkinson's Disease (PD…
Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Data-scarce Medical image segmentation?
Ayush Roy, Samin Enam, Jun Xia +2
Data scarcity is a major challenge in medical imaging, particularly for deep learning models. While data pooling (combining datasets from multiple sources) and data addition (addin…
OCL: Ordinal Contrastive Learning for Imputating Features with Progressive Labels
Seunghun Baek, Jaeyoon Sim, Guorong Wu +1
Accurately discriminating progressive stages of Alzheimer's Disease (AD) is crucial for early diagnosis and prevention. It often involves multiple imaging modalities to understand…