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20222026
most citedCBCT-Based Synthetic CT Image Generation Using Conditional Denoising Diffusion Probabilistic Model

117 citations · 239 across the 36 of their papers we have counts for

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Showing 2025 · cs.CVShow all

9 papers · 2 filters

cs.CV2025

Efficient Vision Mamba for MRI Super-Resolution via Hybrid Selective Scanning

Mojtaba Safari, Shansong Wang, Vanessa L Wildman +10

Background: High-resolution MRI is critical for diagnosis, but long acquisition times limit clinical use. Super-resolution (SR) can enhance resolution post-scan, yet existing deep…

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

Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation

Shansong Wang, Zhecheng Jin, Mingzhe Hu +7

CLIP models pretrained on natural images with billion-scale image-text pairs have demonstrated impressive capabilities in zero-shot classification, cross-modal retrieval, and open-…

cs.CV2025

Limited-Angle CBCT Reconstruction via Geometry-Integrated Cycle-domain Denoising Diffusion Probabilistic Models

Yuan Gao, Shaoyan Pan, Mingzhe Hu +6

Cone-beam CT (CBCT) is widely used in clinical radiotherapy for image-guided treatment, improving setup accuracy, adaptive planning, and motion management. However, slow gantry rot…

cs.CV2025

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning

Mingzhe Hu, Yuan Gao, Yuheng Li +10

Purpose: Accurate segmentation of clinical target volumes (CTV) and organs-at-risk is crucial for optimizing gynecologic brachytherapy (GYN-BT) treatment planning. However, anatomi…

cs.CV2025★ 3 cited

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,…