1 citations · 2 across the 4 of their papers we have counts for
4 papers
HSENet: Hybrid Spatial Encoding Network for 3D Medical Vision-Language Understanding
Yanzhao Shi, Xiaodan Zhang, Junzhong Ji +4
Automated 3D CT diagnosis empowers clinicians to make timely, evidence-based decisions by enhancing diagnostic accuracy and workflow efficiency. While multimodal large language mod…
MEPNet: Medical Entity-balanced Prompting Network for Brain CT Report Generation
Xiaodan Zhang, Yanzhao Shi, Junzhong Ji +2
The automatic generation of brain CT reports has gained widespread attention, given its potential to assist radiologists in diagnosing cranial diseases. However, brain CT scans inv…
A New Federated Learning Framework Against Gradient Inversion Attacks
Pengxin Guo, Shuang Zeng, Wenhao Chen +4
Federated Learning (FL) aims to protect data privacy by enabling clients to collectively train machine learning models without sharing their raw data. However, recent studies demon…
See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning
Chengxin Zheng, Junzhong Ji, Yanzhao Shi +2
Brain CT report generation is significant to aid physicians in diagnosing cranial diseases. Recent studies concentrate on handling the consistency between visual and textual pathol…