42 citations · 93 across the 14 of their papers we have counts for
14 papers
Cross-Subject Emotion Recognition with Sparsely-Labeled Peripheral Physiological Data Using SHAP-Explained Tree Ensembles
Feng Zhou, Tao Chen, Baiying Lei
There are still many challenges of emotion recognition using physiological data despite the substantial progress made recently. In this paper, we attempted to address two major cha…
A Prior Guided Adversarial Representation Learning and Hypergraph Perceptual Network for Predicting Abnormal Connections of Alzheimer's Disease
Qiankun Zuo, Baiying Lei, Shuqiang Wang +3
Alzheimer's disease is characterized by alterations of the brain's structural and functional connectivity during its progressive degenerative processes. Existing auxiliary diagnost…
DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's disease
Junren Pan, Baiying Lei, Shuqiang Wang +3
One of the main reasons for Alzheimer's disease (AD) is the disorder of some neural circuits. Existing methods for AD prediction have achieved great success, however, detecting abn…
Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis
Junren Pan, Baiying Lei, Yanyan Shen +3
Using multimodal neuroimaging data to characterize brain network is currently an advanced technique for Alzheimer's disease(AD) Analysis. Over recent years the neuroimaging communi…
Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction
Qiankun Zuo, Baiying Lei, Yanyan Shen +3
Multimodal neuroimage can provide complementary information about the dementia, but small size of complete multimodal data limits the ability in representation learning. Moreover,…
A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction
Bowen Hu, Baiying Lei, Yanyan Shen +2
Fusing medical images and the corresponding 3D shape representation can provide complementary information and microstructure details to improve the operational performance and accu…
Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation
Mohammad Hamghalam, Alejandro F. Frangi, Baiying Lei +1
In large studies involving multi protocol Magnetic Resonance Imaging (MRI), it can occur to miss one or more sub-modalities for a given patient owing to poor quality (e.g. imaging…
Convolutional 3D to 2D Patch Conversion for Pixel-wise Glioma Segmentation in MRI Scans
Mohammad Hamghalam, Baiying Lei, Tianfu Wang
Structural magnetic resonance imaging (MRI) has been widely utilized for analysis and diagnosis of brain diseases. Automatic segmentation of brain tumors is a challenging task for…
Constrained Multi-shape Evolution for Overlapping Cytoplasm Segmentation
Youyi Song, Lei Zhu, Baiying Lei +4
Segmenting overlapping cytoplasm of cells in cervical smear images is a clinically essential task, for quantitatively measuring cell-level features in order to diagnose cervical ca…
CNN in CT Image Segmentation: Beyound Loss Function for Expoliting Ground Truth Images
Youyi Song, Zhen Yu, Teng Zhou +4
Exploiting more information from ground truth (GT) images now is a new research direction for further improving CNN's performance in CT image segmentation. Previous methods focus o…
A deep network for sinogram and CT image reconstruction
Wei Wang, Xiang-Gen Xia, Chuanjiang He +4
A CT image can be well reconstructed when the sampling rate of the sinogram satisfies the Nyquist criteria and the sampled signal is noise-free. However, in practice, the sinogram…
SANet:Superpixel Attention Network for Skin Lesion Attributes Detection
Xinzi He, Baiying Lei, Tianfu Wang
The accurate detection of lesion attributes is meaningful for both the computeraid diagnosis system and dermatologists decisions. However, unlike lesion segmentation and melenoma c…
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans
Mohammad Hamghalam, Baiying Lei, Tianfu Wang
The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of heal…
Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model
Feng Zhou, Shu Kong, Charless Fowlkes +2
Automated facial expression analysis has a variety of applications in human-computer interaction. Traditional methods mainly analyze prototypical facial expressions of no more than…