76 citations · 192 across the 15 of their papers we have counts for
21 papers
Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Vishnu M. Bashyam, Jimit Doshi, Guray Erus +24
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and…
MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision
Hongming Li, Yong Fan
We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks (FCNs) under a…
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…
Feature-Fused Context-Encoding Network for Neuroanatomy Segmentation
Yuemeng Li, Hangfan Liu, Hongming Li +1
Automatic segmentation of fine-grained brain structures remains a challenging task. Current segmentation methods mainly utilize 2D and 3D deep neural networks. The 2D networks take…