1 citations · 1 across the 2 of their papers we have counts for
5 papers
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…
GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning
Yanzhou Su, Tianbin Li, Jiyao Liu +15
Recent advances in general medical AI have made significant strides, but existing models often lack the reasoning capabilities needed for complex medical decision-making. This pape…
Towards Interpretable Counterfactual Generation via Multimodal Autoregression
Chenglong Ma, Yuanfeng Ji, Jin Ye +6
Counterfactual medical image generation enables clinicians to explore clinical hypotheses, such as predicting disease progression, facilitating their decision-making. While existin…
SegBook: A Simple Baseline and Cookbook for Volumetric Medical Image Segmentation
Jin Ye, Ying Chen, Yanjun Li +7
Computed Tomography (CT) is one of the most popular modalities for medical imaging. By far, CT images have contributed to the largest publicly available datasets for volumetric med…
GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI
Tianbin Li, Yanzhou Su, Wei Li +15
Despite significant advancements in general AI, its effectiveness in the medical domain is limited by the lack of specialized medical knowledge. To address this, we formulate GMAI-…