5 papers
A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation
Haibo Jin, Haoxuan Che, Sunan He +1
Despite the progress of radiology report generation (RRG), existing works face two challenges: 1) The performances in clinical efficacy are unsatisfactory, especially for lesion at…
LLM-driven Medical Report Generation via Communication-efficient Heterogeneous Federated Learning
Haoxuan Che, Haibo Jin, Zhengrui Guo +3
LLMs have demonstrated significant potential in Medical Report Generation (MRG), yet their development requires large amounts of medical image-report pairs, which are commonly scat…
Large Language Model with Region-guided Referring and Grounding for CT Report Generation
Zhixuan Chen, Yequan Bie, Haibo Jin +1
Computed tomography (CT) report generation is crucial to assist radiologists in interpreting CT volumes, which can be time-consuming and labor-intensive. Existing methods primarily…
FedDAG: Federated Domain Adversarial Generation Towards Generalizable Medical Image Analysis
Haoxuan Che, Yifei Wu, Haibo Jin +2
Federated domain generalization aims to train a global model from multiple source domains and ensure its generalization ability to unseen target domains. Due to the target domain b…
Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-training
Tongkun Su, Jun Li, Xi Zhang +6
Multimodal pre-training demonstrates its potential in the medical domain, which learns medical visual representations from paired medical reports. However, many pre-training tasks…