12 citations · 13 across the 12 of their papers we have counts for
15 papers
Non-uniform B-spline optimization method for generating swept surfaces
Xiaoyan Kui, Min Yang, Songpeng Yao +4
Swept surface construction is widely used in computer-aided design. We propose a novel optimization method using non-uniform B-splines to improve the approximate accuracy of swept…
PAS-Mamba: Phase-Amplitude-Spatial State Space Model for MRI Reconstruction
Xiaoyan Kui, Zijie Fan, Zexin Ji +5
Joint feature modeling in both the spatial and frequency domains has become a mainstream approach in MRI reconstruction. However, existing methods generally treat the frequency dom…
Flip Distribution Alignment VAE for Multi-Phase MRI Synthesis
Xiaoyan Kui, Qianmu Xiao, Qqinsong Li +3
Separating shared and independent features is crucial for multi-phase contrast-enhanced (CE) MRI synthesis. However, existing methods use deep autoencoder generators with low param…
An Efficient Model-Driven Groupwise Approach for Atlas Construction
Ziwei Zou, Bei Zou, Xiaoyan Kui +6
Atlas construction is fundamental to medical image analysis, offering a standardized spatial reference for tasks such as population-level anatomical modeling. While data-driven reg…
TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting
Xiaoyan Kui, Canwei Liu, Qinsong Li +4
Kolmogorov-Arnold Networks (KANs) are highly effective in long-term time series forecasting due to their ability to efficiently represent nonlinear relationships and exhibit local…
Mamba Based Feature Extraction And Adaptive Multilevel Feature Fusion For 3D Tumor Segmentation From Multi-modal Medical Image
Zexin Ji, Beiji Zou, Xiaoyan Kui +3
Multi-modal 3D medical image segmentation aims to accurately identify tumor regions across different modalities, facing challenges from variations in image intensity and tumor morp…
Iterative Collaboration Network Guided By Reconstruction Prior for Medical Image Super-Resolution
Xiaoyan Kui, Zexin Ji, Beiji Zou +5
High-resolution medical images can provide more detailed information for better diagnosis. Conventional medical image super-resolution relies on a single task which first performs…
Global and Local Mamba Network for Multi-Modality Medical Image Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
Convolutional neural networks and Transformer have made significant progresses in multi-modality medical image super-resolution. However, these methods either have a fixed receptiv…
A Comprehensive Survey on Magnetic Resonance Image Reconstruction
Xiaoyan Kui, Zijie Fan, Zexin Ji +4
Magnetic resonance imaging (MRI) reconstruction is a fundamental task aimed at recovering high-quality images from undersampled or low-quality MRI data. This process enhances diagn…
Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
In this paper, we propose a self-prior guided Mamba-UNet network (SMamba-UNet) for medical image super-resolution. Existing methods are primarily based on convolutional neural netw…
Deform-Mamba Network for MRI Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
In this paper, we propose a new architecture, called Deform-Mamba, for MR image super-resolution. Unlike conventional CNN or Transformer-based super-resolution approaches which enc…
Ada-DF: An Adaptive Label Distribution Fusion Network For Facial Expression Recognition
Shu Liu, Yan Xu, Tongming Wan +1
Facial expression recognition (FER) plays a significant role in our daily life. However, annotation ambiguity in the datasets could greatly hinder the performance. In this paper, w…
ChebMixer: Efficient Graph Representation Learning with MLP Mixer
Xiaoyan Kui, Haonan Yan, Qinsong Li +2
Graph neural networks have achieved remarkable success in learning graph representations, especially graph Transformer, which has recently shown superior performance on various gra…
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data
Tianyang Zhong, Wei Zhao, Yutong Zhang +39
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and d…
Lightweight Facial Attractiveness Prediction Using Dual Label Distribution
Shu Liu, Enquan Huang, Ziyu Zhou +4
Facial attractiveness prediction (FAP) aims to assess facial attractiveness automatically based on human aesthetic perception. Previous methods using deep convolutional neural netw…