76 citations · 187 across the 20 of their papers we have counts for
5 papers · 1 filter
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…
A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal MRI
Hongming Li, Mohamad Habes, David A. Wolk +1
Introduction: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's dise…
Fully-automatic segmentation of kidneys in clinical ultrasound images using a boundary distance regression network
Shi Yin, Zhengqiang Zhang, Hongming Li +5
It remains challenging to automatically segment kidneys in clinical ultrasound images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic m…
Early Prediction of Alzheimer's Disease Dementia Based on Baseline Hippocampal MRI and 1-Year Follow-Up Cognitive Measures Using Deep Recurrent Neural Networks
Hongming Li, Yong Fan
Multi-modal biological, imaging, and neuropsychological markers have demonstrated promising performance for distinguishing Alzheimer's disease (AD) patients from cognitively normal…
Deep Convolutional Neural Networks for Imaging Data Based Survival Analysis of Rectal Cancer
Hongming Li, Pamela Boimel, James Janopaul-Naylor +4
Recent radiomic studies have witnessed promising performance of deep learning techniques in learning radiomic features and fusing multimodal imaging data. Most existing deep learni…