10 papers · 1 filter
Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model
Zach Eidex, Mojtaba Safari, Tonghe Wang +6
Purpose: Ultra-high-field 7T MRI offers improved resolution and contrast over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce a…
An Efficient 3D Latent Diffusion Model for T1-contrast Enhanced MRI Generation
Zach Eidex, Mojtaba Safari, Jie Ding +7
Objective: Gadolinium-based contrast agents (GBCAs) are commonly employed with T1w MRI to enhance lesion visualization but are restricted in patients at risk of nephrogenic systemi…
Systematic Review and Meta-analysis of AI-driven MRI Motion Artifact Detection and Correction
Mojtaba Safari, Zach Eidex, Richard L. J. Qiu +3
Background: To systematically review and perform a meta-analysis of artificial intelligence (AI)-driven methods for detecting and correcting magnetic resonance imaging (MRI) motion…
Res-MoCoDiff: Residual-guided diffusion models for motion artifact correction in brain MRI
Mojtaba Safari, Shansong Wang, Qiang Li +5
Objective. Motion artifacts in brain MRI, mainly from rigid head motion, degrade image quality and hinder downstream applications. Conventional methods to mitigate these artifacts,…
Benchmarking GPT-5 for Zero-Shot Multimodal Medical Reasoning in Radiology and Radiation Oncology
Mingzhe Hu, Zach Eidex, Shansong Wang +3
Radiology, radiation oncology, and medical physics require decision-making that integrates medical images, textual reports, and quantitative data under high-stakes conditions. With…
Is ChatGPT-5 Ready for Mammogram VQA?
Qiang Li, Shansong Wang, Mingzhe Hu +3
Mammogram visual question answering (VQA) integrates image interpretation with clinical reasoning and has potential to support breast cancer screening. We systematically evaluated…