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20212026
most citedNexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation

5 citations · 8 across the 24 of their papers we have counts for

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9 papers · 1 filter

cs.CV2025★ 1 cited

HippMetric: A skeletal-representation-based framework for cross-sectional and longitudinal hippocampal substructural morphometry

Na Gao, Chenfei Ye, Yanwu Yang +7

Accurate characterization of hippocampal substructure is crucial for detecting subtle structural changes and identifying early neurodegenerative biomarkers. However, high inter-sub…

cs.CL2025

Rewiring Experts on the Fly:Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert models

Guinan Su, Yanwu Yang, Li Shen +3

Mixture-of-Experts (MoE) models achieve efficient scaling through sparse expert activation, but often suffer from suboptimal routing decisions due to distribution shifts in deploym…

cs.CV2025

Efficient Universal Models for Medical Image Segmentation via Weakly Supervised In-Context Learning

Jiesi Hu, Yanwu Yang, Zhiyu Ye +4

Universal models for medical image segmentation, such as interactive and in-context learning (ICL) models, offer strong generalization but require extensive annotations. Interactiv…

cs.CV2025

Towards Robust In-Context Learning for Medical Image Segmentation via Data Synthesis

Jiesi Hu, Yanwu Yang, Zhiyu Ye +4

The rise of In-Context Learning (ICL) for universal medical image segmentation has introduced an unprecedented demand for large-scale, diverse datasets for training, exacerbating t…

cs.CV2025

Medverse: A Universal Model for Full-Resolution 3D Medical Image Segmentation, Transformation and Enhancement

Jiesi Hu, Jianfeng Cao, Yanwu Yang +4

In-context learning (ICL) offers a promising paradigm for universal medical image analysis, enabling models to perform diverse image processing tasks without retraining. However, c…

cs.CV2025

MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation

Yanwu Yang, Guinan Su, Jiesi Hu +3

Universal medical image segmentation models have emerged as a promising paradigm due to their strong generalizability across diverse tasks, showing great potential for a wide range…

eess.IV2025

Hierarchical Characterization of Brain Dynamics via State Space-based Vector Quantization

Yanwu Yang, Thomas Wolfers

Understanding brain dynamics through functional Magnetic Resonance Imaging (fMRI) remains a fundamental challenge in neuroscience, particularly in capturing how the brain transitio…

cs.CL2025

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching

Guinan Su, Li Shen, Lu Yin +3

Large language models (LLMs) have shown remarkable capabilities in language understanding and generation. However, such impressive capability typically comes with a substantial mod…

eess.IV2025

Neuroverse3D: Developing In-Context Learning Universal Model for Neuroimaging in 3D

Jiesi Hu, Chenfei Ye, Yanwu Yang +5

In-context learning (ICL), a type of universal model, demonstrates exceptional generalization across a wide range of tasks without retraining by leveraging task-specific guidance f…