13 papers
SAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Prediction
Chongyu Qu, Can Cui, Zhengyi Lu +8
Does every cancer patient truly need a complete diagnostic workup for accurate survival prediction? In multimodal clinical oncology, diagnostic modalities follow a clinically manda…
MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations
Leiyue Zhao, Tianyu Shi, Daniel Reisenbuchler +12
Instance-level quantification of kidney functional units is essential for morphometric analysis, yet most publicly available pathology datasets provide only semantic segmentation a…
DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction
Junchao Zhu, Ruining Deng, Junlin Guo +11
Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing methods reduce this task to…
Explainable Pathomics Feature Visualization via Correlation-aware Conditional Feature Editing
Yuechen Yang, Junlin Guo, Ruining Deng +9
Pathomics is a recent approach that offers rich quantitative features beyond what black-box deep learning can provide, supporting more reproducible and explainable biomarkers in di…
MASC: Metal-Aware Sampling and Correction via Reinforcement Learning for Accelerated MRI
Zhengyi Lu, Ming Lu, Chongyu Qu +11
Metal implants in MRI cause severe artifacts that degrade image quality and hinder clinical diagnosis. Traditional approaches address metal artifact reduction (MAR) and accelerated…
AdaFuse: Adaptive Multimodal Fusion for Lung Cancer Risk Prediction via Reinforcement Learning
Chongyu Qu, Zhengyi Lu, Yuxiang Lai +10
Multimodal fusion has emerged as a promising paradigm for disease diagnosis and prognosis, integrating complementary information from heterogeneous data sources such as medical ima…