6 papers
Spatio-Temporal and Clinical Conditioning for Fine-Grained Radiology Report Retrieval
P. Sloan, E. Simpson, M. Mirmehdi
Radiology is vital to modern healthcare, but rising imaging demand and persistent workforce shortages strain reporting capacity and clinical workflows. Automated radiology report g…
DiffGraph: An Automated Agent-driven Model Merging Framework for In-the-Wild Text-to-Image Generation
Zhuoling Li, Hossein Rahmani, Jiarui Zhang +5
The rapid growth of the text-to-image (T2I) community has fostered a thriving online ecosystem of expert models, which are variants of pretrained diffusion models specialized for d…
When Visual Privacy Protection Meets Multimodal Large Language Models
Xiaofei Hui, Qian Wu, Haoxuan Qu +3
The emergence of Multimodal Large Language Models (MLLMs) and the widespread usage of MLLM cloud services such as GPT-4V raised great concerns about privacy leakage in visual data.…
LEMON: Local Explanations via Modality-aware OptimizatioN
Yu Qin, Phillip Sloan, Raul Santos-Rodriguez +2
Multimodal models are ubiquitous, yet existing explainability methods are often single-modal, architecture-dependent, or too computationally expensive to run at scale. We introduce…
Clinically-aligned Multi-modal Chest X-ray Classification
Phillip Sloan, Edwin Simpson, Majid Mirmehdi
Radiology is essential to modern healthcare, yet rising demand and staffing shortages continue to pose major challenges. Recent advances in artificial intelligence have the potenti…
Automatic Prediction of Stroke Treatment Outcomes: Latest Advances and Perspectives
Zeynel A. Samak, Philip Clatworthy, Majid Mirmehdi
Stroke is a major global health problem that causes mortality and morbidity. Predicting the outcomes of stroke intervention can facilitate clinical decision-making and improve pati…