Area of research
Computer Vision and Pattern Recognition · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Computer science, Artificial intelligence, Data science, Multimedia, Computer graphics (images), and Segmentation.
Over 20% Efficient Water‐Based Layer‐by‐Layer Organic Solar Cells with High Thickness Tolerance Enabled by Surfactant Promoted Electrostatic Interaction
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation
Harnessing cell size to separate genetically and functionally distinct dental pulp-derived mesenchymal stromal cell subpopulations
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-training
Bridged Semantic Alignment for Zero-Shot 3D Medical Image Diagnosis
OS-SSVEP: One-shot SSVEP classification
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Histopathological bladder cancer gene mutation prediction with hierarchical deep multiple-instance learning
LE-UDA: Label-Efficient Unsupervised Domain Adaptation for Medical Image Segmentation
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes