2 citations · 4 across the 5 of their papers we have counts for
5 papers
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…
Automating Vessel Segmentation in the Heart and Brain: A Trend to Develop Multi-Modality and Label-Efficient Deep Learning Techniques
Nazik Elsayed, Yousuf Babiker M. Osman, Cheng Li +2
Cardio-cerebrovascular diseases are the leading causes of mortality worldwide, whose accurate blood vessel segmentation is significant for both scientific research and clinical usa…
Collaborative Learning for Annotation-Efficient Volumetric MR Image Segmentation
Yousuf Babiker M. Osman, Cheng Li, Weijian Huang +1
Background: Deep learning has presented great potential in accurate MR image segmentation when enough labeled data are provided for network optimization. However, manually annotati…
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation
Yousuf Babiker M. Osman, Cheng Li, Weijian Huang +4
Volumetric magnetic resonance (MR) image segmentation plays an important role in many clinical applications. Deep learning (DL) has recently achieved state-of-the-art or even human…
Uncertainty-Aware Multi-Parametric Magnetic Resonance Image Information Fusion for 3D Object Segmentation
Cheng Li, Yousuf Babiker M. Osman, Weijian Huang +4
Multi-parametric magnetic resonance (MR) imaging is an indispensable tool in the clinic. Consequently, automatic volume-of-interest segmentation based on multi-parametric MR imagin…