5 papers
A Unified Vision-Language Model for PSMA PET/CT Report Generation, Visual Question Answering, and Lesion Segmentation
Yang Xing, Jiong Wu, Savas Ozdemir +11
Accurate PSMA PET/CT interpretation is central to prostate cancer management, yet existing PET/CT AI models typically address isolated tasks. We propose a unified PSMA PET/CT visio…
VLM- and LLM-Driven Multi-Agent System for PET Image Denoising
Boxiao Yu, Savas Ozdemir, Yang Xing +8
Positron emission tomography (PET) imaging suffers from limited spatial resolution and low signal-to-noise ratio, which can compromise quantitative accuracy and lesion detectabilit…
MedVL-SAM2: A unified 3D medical vision-language model for multimodal reasoning and prompt-driven segmentation
Yang Xing, Jiong Wu, Savas Ozdemir +4
Recent progress in medical vision-language models (VLMs) has achieved strong performance on image-level text-centric tasks such as report generation and visual question answering (…
Patlak Parametric Image Estimation from Dynamic PET Using Diffusion Model Prior
Ziqian Huang, Boxiao Yu, Siqi Li +5
Dynamic PET enables the quantitative estimation of physiology-related parameters and is widely utilized in research and increasingly adopted in clinical settings. Parametric imagin…
PET Image Denoising via Text-Guided Diffusion: Integrating Anatomical Priors through Text Prompts
Boxiao Yu, Savas Ozdemir, Jiong Wu +4
Low-dose Positron Emission Tomography (PET) imaging presents a significant challenge due to increased noise and reduced image quality, which can compromise its diagnostic accuracy…