Area of research
Computer Vision and Pattern Recognition · Computational Mechanics
Research interest
Research interests include Medical Image Segmentation Techniques, Image and Signal Denoising Methods, Sparse and Compressive Sensing Techniques, and Electromagnetic Scattering and Analysis.
An effective deep learning algorithm for medical image registration.
Effects of Different Nitrogen Substitution Practices on Nitrogen Utilization, Surplus, and Footprint in the Sweet Maize Cropping System in South China
A Novel Few-Shot Learning Framework for Supervised Diffeomorphic Image Registration Network.
Ricci Curvature Tensor-Based Volumetric Segmentation.
Selecting projection views based on error equidistribution for computed tomography.
Unsupervised Low-Dose CT Reconstruction With One-Way Conditional Normalizing Flows
Vectorial Fractional-Order Regularizer-Based Diffeomorphic Image Registration Model and its Numerical Algorithm
CA-Net: a context-awareness and cross-channel attention-based network for point cloud understanding
A bi-variant variational model for diffeomorphic image registration with relaxed Jacobian determinant constraints
MVMS-RCN: A Dual-Domain Unified CT Reconstruction With Multi-Sparse-View and Multi-Scale Refinement-Correction
Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma.
Ricci curvature based volumetric segmentation
Time multiscale regularization for nonlinear image registration.
Self-supervised dual-domain balanced dropblock-network for low-dose CT denoising.
Multiscale Approach for Variational Problem Joint Diffeomorphic Image Registration and Intensity Correction: Theory and Application
A semi-automatic segmentation method for meningioma developed using a variational approach model.
Breaking the limitations with sparse inputs by variational frameworks (BLIss) in terahertz super-resolution 3D reconstruction.
DaISy: diffuser-aided sub-THz imaging system.
Nest-DGIL: Nesterov-Optimized Deep Geometric Incremental Learning for CS Image Reconstruction
Image Segmentation Based on the Hybrid Bias Field Correction
Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP).
Fast Multi-Grid Methods for Minimizing Curvature Energies.
Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning.
Vascular Lakes in Uveal Melanoma and Their Association With Outcome.
Arterial input function segmentation based on a contour geodesic model for tissue at risk identification in ischemic stroke.
Optimal Scaling Approaches for Perfusion MRI with Distorted Arterial Input Function (AIF) in Patients with Ischemic Stroke.
A two-level method for image denoising and image deblurring models using mean curvature regularization
A Generalized Asymmetric Dual-Front Model for Active Contours and Image Segmentation.
On a Variational and Convex Model of the Blake-Zisserman Type for Segmentation of Low-Contrast and Piecewise Smooth Images.