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cs.CV2026

Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary

Alexandru Florea, Shansong Wang, Mingzhe Hu +5

The transition from task-specific artificial intelligence toward general-purpose foundation models raises fundamental questions about their capacity to support the integrated reaso…

cs.CV2025

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,…

cs.CV2025

DINOv3 with Test-Time Training for Medical Image Registration

Shansong Wang, Mojtaba Safari, Mingzhe Hu +4

Prior medical image registration approaches, particularly learning-based methods, often require large amounts of training data, which constrains clinical adoption. To overcome this…

cs.CV2025

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…

cs.CV2025

Performance of GPT-5 in Brain Tumor MRI Reasoning

Mojtaba Safari, Shansong Wang, Mingzhe Hu +3

Accurate differentiation of brain tumor types on magnetic resonance imaging (MRI) is critical for guiding treatment planning in neuro-oncology. Recent advances in large language mo…

cs.CV2025

MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting

Mojtaba Safari, Shansong Wang, Zach Eidex +4

Objective:This study introduces a residual error-shifting mechanism that drastically reduces sampling steps while preserving critical anatomical details, thus accelerating MRI reco…