2 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
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…
A Comprehensive Survey of Foundation Models in Medicine
Wasif Khan, Seowung Leem, Kyle B. See +3
Foundation models (FMs) are large-scale deep learning models trained on massive datasets, often using self-supervised learning techniques. These models serve as a versatile base fo…
BrainSegFounder: Towards 3D Foundation Models for Neuroimage Segmentation
Joseph Cox, Peng Liu, Skylar E. Stolte +5
The burgeoning field of brain health research increasingly leverages artificial intelligence (AI) to interpret and analyze neurological data. This study introduces a novel approach…