1 citations · 1 across the 6 of their papers we have counts for
7 papers
DINO-Med: A Unified Patch-Based Adaptation Framework for Multi-Modal Medical Image Analysis Applied to Liver Fibrosis Staging
Boya Wang, Ruizhe Li, Chao Chen +1
Adapting natural-image foundation models like DINOv3 to multi-modal medical imaging is challenging due to the significant domain gap between natural color images and multi-channel…
Semi-supervised Liver Segmentation and Patch-based Fibrosis Staging with Registration-aided Multi-parametric MRI
Boya Wang, Ruizhe Li, Chao Chen +1
Liver fibrosis poses a substantial challenge in clinical practice, emphasizing the necessity for precise liver segmentation and accurate disease staging. Based on the CARE Liver 20…
Standardizing Longitudinal Radiology Report Evaluation via Large Language Model Annotation
Xinyi Wang, Grazziela Figueredo, Ruizhe Li +1
Longitudinal information in radiology reports refers to the sequential tracking of findings across multiple examinations over time, which is crucial for monitoring disease progress…
Breast Cancer Neoadjuvant Chemotherapy Treatment Response Prediction Using Aligned Longitudinal MRI and Clinical Data
Rahul Ravi, Ruizhe Li, Tarek Abdelfatah +2
Aim: This study investigates treatment response prediction to neoadjuvant chemotherapy (NACT) in breast cancer patients, using longitudinal contrast-enhanced magnetic resonance ima…
A Unified Framework for Semi-Supervised Image Segmentation and Registration
Ruizhe Li, Grazziela Figueredo, Dorothee Auer +3
Semi-supervised learning, which leverages both annotated and unannotated data, is an efficient approach for medical image segmentation, where obtaining annotations for the whole da…
MrRegNet: Multi-resolution Mask Guided Convolutional Neural Network for Medical Image Registration with Large Deformations
Ruizhe Li, Grazziela Figueredo, Dorothee Auer +2
Deformable image registration (alignment) is highly sought after in numerous clinical applications, such as computer aided diagnosis and disease progression analysis. Deep Convolut…
A Survey of Deep Learning-based Radiology Report Generation Using Multimodal Data
Xinyi Wang, Grazziela Figueredo, Ruizhe Li +3
Automatic radiology report generation can alleviate the workload for physicians and minimize regional disparities in medical resources, therefore becoming an important topic in the…