111 citations · 210 across the 22 of their papers we have counts for
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3D Wavelet Latent Diffusion Model for Whole-Body MR-to-CT Modality Translation
Jiaxu Zheng, Meiman He, Xuhui Tang +5
Magnetic Resonance (MR) imaging plays an essential role in contemporary clinical diagnostics. It is increasingly integrated into advanced therapeutic workflows, such as hybrid Posi…
REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation
Zhiyun Song, Yinjie Zhao, Xiaomin Li +9
High-resolution (HR) 3D magnetic resonance imaging (MRI) can provide detailed anatomical structural information, enabling precise segmentation of regions of interest for various me…
Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning
Xin Wang, Zhiyun Song, Yitao Zhu +4
In clinical practice, 2D magnetic resonance (MR) sequences are widely adopted. While individual 2D slices can be stacked to form a 3D volume, the relatively large slice spacing can…
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images
Zhiyun Song, Zengxin Qi, Xin Wang +11
Cross-modality synthesis (CMS), super-resolution (SR), and their combination (CMSR) have been extensively studied for magnetic resonance imaging (MRI). Their primary goals are to e…
Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening
Jiangdong Cai, Honglin Xiong, Maosong Cao +3
Vulvovaginal candidiasis (VVC) is the most prevalent human candidal infection, estimated to afflict approximately 75% of all women at least once in their lifetime. It will lead to…
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
Xiangyu Zhao, Sheng Wang, Zhiyun Song +5
Accurate automatic segmentation of medical images typically requires large datasets with high-quality annotations, making it less applicable in clinical settings due to limited tra…
CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning
Yuqi Hu, Xiangyu Zhao, Gaowei Qing +3
Background: MR-based subchondral bone effectively predicts knee osteoarthritis. However, its clinical application is limited by the cost and time of MR. Purpose: We aim to develop…
Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion
Xin Wang, Zhenrong Shen, Zhiyun Song +5
Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resoluti…
TBI-GAN: An Adversarial Learning Approach for Data Synthesis on Traumatic Brain Segmentation
Xiangyu Zhao, Di Zang, Sheng Wang +10
Brain network analysis for traumatic brain injury (TBI) patients is critical for its consciousness level assessment and prognosis evaluation, which requires the segmentation of cer…
Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing
Xin Wang, Sheng Wang, Honglin Xiong +7
Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resoluti…
Knee Cartilage Defect Assessment by Graph Representation and Surface Convolution
Zixu Zhuang, Liping Si, Sheng Wang +8
Knee osteoarthritis (OA) is the most common osteoarthritis and a leading cause of disability. Cartilage defects are regarded as major manifestations of knee OA, which are visible b…
Multi-Modal MRI Reconstruction Assisted with Spatial Alignment Network
Kai Xuan, Lei Xiang, Xiaoqian Huang +4
In clinical practice, multi-modal magnetic resonance imaging (MRI) with different contrasts is usually acquired in a single study to assess different properties of the same region…
A Self-ensembling Framework for Semi-supervised Knee Cartilage Defects Assessment with Dual-Consistency
Jiayu Huo, Liping Si, Xi Ouyang +6
Knee osteoarthritis (OA) is one of the most common musculoskeletal disorders and requires early-stage diagnosis. Nowadays, the deep convolutional neural networks have achieved grea…
Reducing Magnetic Resonance Image Spacing by Learning Without Ground-Truth
Kai Xuan, Liping Si, Lichi Zhang +6
High-quality magnetic resonance (MR) image, i.e., with near isotropic voxel spacing, is desirable in various scenarios of medical image analysis. However, many MR acquisitions use…
Robust Brain Magnetic Resonance Image Segmentation for Hydrocephalus Patients: Hard and Soft Attention
Xuhua Ren, Jiayu Huo, Kai Xuan +3
Brain magnetic resonance (MR) segmentation for hydrocephalus patients is considered as a challenging work. Encoding the variation of the brain anatomical structures from different…
Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
Xuhua Ren, Lichi Zhang, Qian Wang +1
Medical image segmentation is challenging especially in dealing with small dataset of 3D MR images. Encoding the variation of brain anatomical struc-tures from individual subjects…