Team

SHEN Zhenrong

• Controllable Medical Image Synthesis Framework for Cross-Modality Normal Anatomy Representation and Parametric Disease Progression Modeling

LIU Mengjun

• Deep Learning Framework for Functional Connectivity Pattern Encoding in fMRI: Extracting Neurobiological Signatures for Depression Diagnosis and Treatment Response Prediction

XIONG Honglin

• Developing MRI Foundation Models: Unifying Contrast Interactions for Universal Medical Image Synthesis and Processing

LI Feng

• Deep Learning-Based Motion Artifact Detection and Correction for Quantitative Quality Assessment in Neuroimaging MRI

GUO Jiayang

• Multimodal Cohort Development and Data Integration for Longitudinal Assessment of Neurodevelopmental Trajectories in Pediatric Populations

WANG Zhixin

• Comprehensive Phenotyping Through Multimodal Biomarker Acquisition and Analysis for Characterization of Neurodevelopmental Patterns in Children

ZHU Yitao

• Computational 3D Human Modeling for Quantitative Assessment of Motor Development and Behavioral Phenotyping in Pediatric Neurocognitive Research

FANG Yu

• Multimodal Brain Image Acquisition and Temporal Completion: Deep Learning Framework for Reconstructing Missing Data and Modeling Longitudinal Neurodevelopmental Trajectories in Pediatric Populations

CAI Jiangdong

• Deep Learning-Based Cellular Morphology Analysis for Automated TCT Image Classification and Cervical Cancer Screening

LI Zongyu

• FPGA-Accelerated Surgical Guidance System: Hardware-Optimized Deep Learning Framework for Real-Time Medical Device Integration and Clinical Validation

TANG Yuxian

• Comprehensive MRI Quality Enhancement: Unified Framework for Multi-Source Distortion Correction Beyond Motion Artifacts in Neuroimaging

WANG Xinyu

• Deep Learning Foundation Model for fMRI BOLD Signal Encoding: Developing Generalizable Representations for Cross-Subject Analysis and Neurobiological Marker Extraction in Clinical Applications

XU Mengjie

• Computational Modeling of Object Properties and Human-Object Interactions for Cognitive Development Assessment in Pediatric Neurobehavioral Studies

JIANG Haotian

• Unified Foundation Model for TCT Image Analysis: Integrating Multi-Scale Features for Robust Cervical Cancer Detection and Classification

HUANG Haolin

• Multimodal PET Data Integration and Analysis for Neurodegenerative Disease Assessment: Deep Learning Approaches for Quantitative Biomarker Extraction and Personalized Prognosis Prediction

CHEN Yan

• Efficient Generative Modeling Architectures for Medical Imaging: Optimized Frameworks for Clinical-Grade Image Enhancement and Whole-Body Segmentation

LI Jiaming

• Adaptive Human-Machine Interaction System for Clinical Decision Support: Integrating AI-Driven Diagnostic Tools within Established Healthcare Workflows for Enhanced Treatment Planning and Patient Outcomes

SONG Haiyu

• Comprehensive Foundation Models for Musculoskeletal MRI: Integrated Approaches for Multi-Disease Pathology Detection and Progression Modeling Using Transferable Deep Learning Architectures

WU Junlei

• Real-Time Image Quality Preservation in Interactive Clinical Systems: Computational Methods for Addressing Degradation Challenges during Human-Machine Collaborative Diagnosis and Treatment

ZHONG Aocheng

• Advanced Reconstruction and Quality Enhancement Framework for PET-MR Imaging: AI-Driven Techniques for Improved Detection of Neurodegenerative Disease Biomarkers

KONG Yan

YIN Yuan

ZHOU Jiarui