Convolutional neural networks (CNNs) have been widely used to build deep...
To achieve fast, robust, and accurate reconstruction of the human cortic...
Conventional survival analysis methods are typically ineffective to
char...
Purpose: To accelerate radially sampled diffusion weighted spin-echo
(Ra...
Neuroimaging biomarkers that distinguish between typical brain aging and...
A novel unsupervised deep learning method is developed to identify
indiv...
Neural network has been recognized with its accomplishments on tackling
...
Conventional and deep learning-based methods have shown great potential ...
We present a diffeomorphic image registration algorithm to learn spatial...
Deep learning in k-space has demonstrated great potential for image
reco...
Segmentation of brain structures from magnetic resonance (MR) scans play...
Skull stripping is usually the first step for most brain analysisprocess...
Automatic segmentation of fine-grained brain structures remains a challe...
Introduction: It is challenging at baseline to predict when and which
in...
Pulmonary nodule detection plays an important role in lung cancer screen...
It remains challenging to automatically segment kidneys in clinical
ultr...
Multi-modal biological, imaging, and neuropsychological markers have
dem...
Recent radiomic studies have witnessed promising performance of deep lea...
It remains challenging to automatically segment kidneys in clinical
ultr...
Decoding brain functional states underlying different cognitive processe...
Dynamic functional connectivity analysis provides valuable information f...
We present a deep semi-nonnegative matrix factorization method for
ident...
Brain age prediction based on neuroimaging data could help characterize ...
A novel non-rigid image registration algorithm is built upon fully
convo...
Classification of ultrasound (US) kidney images for diagnosis of congeni...
A novel multi-atlas based image segmentation method is proposed by
integ...
Increasing effort in brain image analysis has been dedicated to early
di...
Purpose: To improve kidney segmentation in clinical ultrasound (US) imag...
In this paper, we propose a novel sparse learning based feature selectio...