Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Artificial intelligence, Deep learning, Segmentation, Cancer research, and Pattern recognition (psychology).
Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR
Synthesis of hydrogel of polyvinylimide modified carboxylated nanocellulose combined with acidified montmorillonite for pH-controlled release of thiamethoxam
RecON: Online learning for sensorless freehand 3D ultrasound reconstruction
Temperature-Sensitive Aerogel Using Bagasse Carboxylated Cellulose Nanocrystals/N-Isopropyl Acrylamide for Controlled Release of Pesticides
AWSnet: An auto-weighted supervision attention network for myocardial scar and edema segmentation in multi-sequence cardiac magnetic resonance images
Extracting keyframes of breast ultrasound video using deep reinforcement learning
Dual-Modality Molecular Imaging of Tumor via Quantum Dots-Liposome–Microbubble Complexes
Leronlimab, a humanized monoclonal antibody to CCR5, blocks breast cancer cellular metastasis and enhances cell death induced by DNA damaging chemotherapy
Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging
Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound
Arterial Spin Labeling Images Synthesis From sMRI Using Unbalanced Deep Discriminant Learning
Shuxuening injection protects against myocardial ischemia-reperfusion injury through reducing oxidative stress, inflammation and thrombosis
Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans
KLF6 Suppresses Metastasis of Clear Cell Renal Cell Carcinoma via Transcriptional Repression of E2F1