25 citations · 40 across the 9 of their papers we have counts for
5 papers · 1 filter
Medical Image Segmentation with Domain Adaptation: A Survey
Yuemeng Li, Yong Fan
Deep learning (DL) has shown remarkable success in various medical imaging data analysis applications. However, it remains challenging for DL models to achieve good generalization,…
Learning Apparent Diffusion Coefficient Maps from Accelerated Radial k-Space Diffusion-Weighted MRI in Mice using a Deep CNN-Transformer Model
Yuemeng Li, Miguel Romanello Joaquim, Stephen Pickup +3
Purpose: To accelerate radially sampled diffusion weighted spin-echo (Rad-DW-SE) acquisition method for generating high quality apparent diffusion coefficient (ADC) maps. Methods:…
Adaptive convolutional neural networks for k-space data interpolation in fast magnetic resonance imaging
Tianming Du, Honggang Zhang, Yuemeng Li +2
Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep l…
ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation
Yuemeng Li, Hongming Li, Yong Fan
Segmentation of brain structures from magnetic resonance (MR) scans plays an important role in the quantification of brain morphology. Since 3D deep learning models suffer from hig…
Context-endcoding for neural network based skull stripping in magnetic resonance imaging
Zhen Liu, Borui Xiao, Yuemeng Li +1
Skull stripping is usually the first step for most brain analysisprocess in magnetic resonance images. A lot of deep learn-ing neural network based methods have been developed toac…