3 citations · 6 across the 23 of their papers we have counts for
5 papers · 1 filter
Open World MRI Reconstruction with Bias-Calibrated Adaptation
Jiyao Liu, Shangqi Gao, Lihao Liu +5
Real-world MRI reconstruction systems face the open-world challenge: test data from unseen imaging centers, anatomical structures, or acquisition protocols can differ drastically f…
Unified Medical Image Tokenizer for Autoregressive Synthesis and Understanding
Chenglong Ma, Yuanfeng Ji, Jin Ye +9
Autoregressive modeling has driven major advances in multimodal AI, yet its application to medical imaging remains constrained by the absence of a unified image tokenizer that simu…
RetinaLogos: Fine-Grained Synthesis of High-Resolution Retinal Images Through Captions
Junzhi Ning, Cheng Tang, Kaijing Zhou +12
The scarcity of high-quality, labelled retinal imaging data, which presents a significant challenge in the development of machine learning models for ophthalmology, hinders progres…
Ophora: A Large-Scale Data-Driven Text-Guided Ophthalmic Surgical Video Generation Model
Wei Li, Ming Hu, Guoan Wang +7
In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophthalmic surgical videos with high-q…
Multi-modal MRI Translation via Evidential Regression and Distribution Calibration
Jiyao Liu, Shangqi Gao, Yuxin Li +9
Multi-modal Magnetic Resonance Imaging (MRI) translation leverages information from source MRI sequences to generate target modalities, enabling comprehensive diagnosis while overc…