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20232026
most citedMRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting

13 citations · 56 across the 30 of their papers we have counts for

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8 papers · 1 filter

cs.AI2026

A radiographic world model for clinical reasoning and evidence generation

Suyang Xi, Songtao Hu, Shansong Wang +8

Medical imaging artificial intelligence (AI) is commonly developed as separate mappings from radiographs to diagnostic outputs or from clinical descriptions to generated images, al…

cs.CV2026

Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction

Mojtaba Safari, Shansong Wang, Zach Eidex +4

Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitative analysis. Existing deep l…

cs.CV2026

MRI super-resolution in ten sampling steps using a diffusion bridge model

Mojtaba Safari, Hang Yu, Zach Eidex +10

Objective. MRI provides excellent soft-tissue contrast, but long acquisition times can cause patient discomfort and lead to motion artifacts, forcing a trade-off between spatial re…

cs.CV2026

Text-Guided Refinement of Multi-sequence Glioma Subregion Segmentation with a Vision-Language Foundation Model

Zach Eidex, Yu-nong Lin, Mojtaba Safari +4

Background: Accurate glioma subregion delineation is important for radiotherapy planning and longitudinal monitoring, but manual contour correction is time-consuming. Models such a…

physics.med-ph2026

One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy

Shaoyan Pan, Kirk Jon Luca, Yuan Gao +8

In this work, we introduce the One-for-All Adaptive Radiotherapy Planning Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive…

cs.CV2026

Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining

Yuheng Li, Yuan Gao, Haoyu Dong +5

Computed tomography (CT) is a central to three-dimensional medical imaging, yet CT-based artificial intelligence remains fragmented across task-specific models for segmentation, cl…

cs.LG2026

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning

Yizhou Wu, Shansong Wang, Yuheng Li +5

Brain MRI underpins a wide range of neuroscientific and clinical applications, yet most learning-based methods remain task-specific and require substantial labeled data. Here we sh…

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…