activity
20182025
most citedNexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation

5 citations · 8 across the 9 of their papers we have counts for

collaborators

10 papers

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…

cs.CV2024

Advancing Brain Imaging Analysis Step-by-step via Progressive Self-paced Learning

Yanwu Yang, Hairui Chen, Jiesi Hu +2

Recent advancements in deep learning have shifted the development of brain imaging analysis. However, several challenges remain, such as heterogeneity, individual variations, and t…

cs.CV2023

A Chebyshev Confidence Guided Source-Free Domain Adaptation Framework for Medical Image Segmentation

Jiesi Hu, Yanwu Yang, Xutao Guo +2

Source-free domain adaptation (SFDA) aims to adapt models trained on a labeled source domain to an unlabeled target domain without the access to source data. In medical imaging sce…

eess.IV2023★ 5 cited

NexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation

Pengcheng Shi, Xutao Guo, Yanwu Yang +2

Convolutional neural networks (CNN) and Transformer variants have emerged as the leading medical image segmentation backbones. Nonetheless, due to their limitations in either prese…

eess.IV2023

DECOR-NET: A COVID-19 Lung Infection Segmentation Network Improved by Emphasizing Low-level Features and Decorrelating Features

Jiesi Hu, Yanwu Yang, Xutao Guo +1

Since 2019, coronavirus Disease 2019 (COVID-19) has been widely spread and posed a serious threat to public health. Chest Computed Tomography (CT) holds great potential for screeni…

eess.IV2022★ 1 cited

Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation

Xutao Guo, Yanwu Yang, Chenfei Ye +3

Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise…

eess.IV2022

Multi-modal Dynamic Graph Network: Coupling Structural and Functional Connectome for Disease Diagnosis and Classification

Yanwu Yang, Xutao Guo, Zhikai Chang +3

Multi-modal neuroimaging technology has greatlly facilitated the efficiency and diagnosis accuracy, which provides complementary information in discovering objective disease biomar…

eess.IV2022

Estimating Brain Age with Global and Local Dependencies

Yanwu Yang, Xutao Guo, Zhikai Chang +4

The brain age has been proven to be a phenotype of relevance to cognitive performance and brain disease. Achieving accurate brain age prediction is an essential prerequisite for op…

eess.IV2021★ 1 cited

Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net

Yanwu Yang, Xutao Guo, Yiwei Pan +3

Accurate medical image segmentation is crucial for diagnosis and analysis. However, the models without calibrated uncertainty estimates might lead to errors in downstream analysis…

cs.CV2018★ 1 cited

SeFM: A Sequential Feature Point Matching Algorithm for Object 3D Reconstruction

Zhihao Fang, He Ma, Xuemin Zhu +2

3D reconstruction is a fundamental issue in many applications and the feature point matching problem is a key step while reconstructing target objects. Conventional algorithms can…