most citedIterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation

45 citations

7 papers

cs.CV20251 cited

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…

physics.med-ph20251 cited

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…

physics.med-ph20252 cited

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…

cs.CV20251 cited

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…

cs.CV202545 cited

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…

cs.AI20254 cited

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)…