90 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shandong Provincial HospitalCN4 papers
- Shandong Tumor HospitalCN4 papers
- Shandong UniversityCN4 papers
- Al-Neelain UniversitySD2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- Shenzhen Institutes of Advanced TechnologyCN2 papers
- The University of SydneyAU2 papers
- Alpha Omega Alpha Medical Honor SocietyUS1 paper
- Centre de Recherche en Mathématiques de la DécisionFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Chinese Academy of SciencesCN1 paper
- Commonwealth Scientific and Industrial Research OrganisationAU1 paper
11 papers
Unsupervised Anomaly Detection in Brain MRI via Disentangled Anatomy Learning
Tao Yang, Xiuying Wang, Hao Liu +4
Detection of various lesions in brain MRI is clinically critical, but challenging due to the diversity of lesions and variability in imaging conditions. Current unsupervised learni…
Cross-Axis Weighted Harmonic Method: A Frequency-Domain Approach for Enhanced Resolution in Magnetic Particle Imaging
Abuobaida M. khair, Wenjing Jiang, Moritz Wildgruber +2
Magnetic Particle Imaging (MPI) is a promising imaging modality that tracks magnetic nanoparticles (MNPs) to generate real time, high-resolution images. However, achieving an optim…
High-Resolution Magnetic Particle Imaging System Matrix Recovery Using a Vision Transformer with Residual Feature Network
Abuobaida M. Khair, Wenjing Jiang, Yousuf Babiker M. Osman +2
This study presents a hybrid deep learning framework, the Vision Transformer with Residual Feature Network (VRF-Net), for recovering high-resolution system matrices in Magnetic Par…
LatXGen: Towards Radiation-Free and Accurate Quantitative Analysis of Sagittal Spinal Alignment Via Cross-Modal Radiographic View Synthesis
Moxin Zhao, Nan Meng, Jason Pui Yin Cheung +7
Adolescent Idiopathic Scoliosis (AIS) is a complex three-dimensional spinal deformity, and accurate morphological assessment requires evaluating both coronal and sagittal alignment…
Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation
Qiangguo Jin, Hui Cui, Junbo Wang +7
Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-l…
BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning
Yitong Lin, Jiaying He, Jiahe Chen +3
Motivation: Biomedical knowledge graphs (KGs) are crucial for drug discovery and disease understanding, yet their completion and reasoning are challenging. Knowledge Embedding (KE)…
Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration
Liqi Yan, Qifan Wang, Siqi Ma +2
Instance segmentation in videos, which aims to segment and track multiple objects in video frames, has garnered a flurry of research attention in recent years. In this paper, we pr…
Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism
Minghan Fu, Yanhua Duan, Zhaoping Cheng +4
Reducing the radiation exposure for patients in Total-body CT scans has attracted extensive attention in the medical imaging community. Given the fact that low radiation dose may r…
COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19
Guoqing Bao, Huai Chen, Tongliang Liu +4
There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis me…
Geodesic Paths for Image Segmentation with Implicit Region-based Homogeneity Enhancement
Da Chen, Jian Zhu, Xinxin Zhang +2
Minimal paths are regarded as a powerful and efficient tool for boundary detection and image segmentation due to its global optimality and the well-established numerical solutions…
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps
Yuan Xue, Hui Tang, Zhi Qiao +6
In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall sha…