activity
20232025
most citedCycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis

18 citations · 34 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV20251 cited

Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging

Shansong Wang, Mojtaba Safari, Qiang Li +5

Vision foundation models (VFMs) are pre-trained on extensive image datasets to learn general representations for diverse types of data. These models can subsequently be fine-tuned…

eess.IV20241 cited

Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas

Zach Eidex, Mojtaba Safari, Jacob Wynne +6

Purpose: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted (DWI) MRI provides functional measurements about the water molecules in tissues. However, DWI is…

cs.CV20242 cited

Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography

Xuxin Chen, Yuheng Li, Mingzhe Hu +5

Although fusion of information from multiple views of mammograms plays an important role to increase accuracy of breast cancer detection, developing multi-view mammograms-based com…

physics.med-ph20242 cited

Dual-Energy Cone-Beam CT Using Two Complementary Limited-Angle Scans with A Projection-Consistent Diffusion Model

Junbo Peng, Chih-Wei Chang, Richard L. J. Qiu +5

Background: Dual-energy imaging on cone-beam CT (CBCT) scanners has great potential in different clinical applications, including image-guided surgery and adaptive proton therapy.…

physics.med-ph2024

Assessing Bilateral Neurovascular Bundles Function with Pulsed Wave Doppler Ultrasound: Implications for Reducing Erectile Dysfunction Following Prostate Radiotherapy

Jing Wang, Xiaofeng Yang, Boran Zhou +5

This study aims to evaluate the functional status of bilateral neurovascular bundles (NVBs) using pulsed wave Doppler ultrasound in patients undergoing prostate radiotherapy (RT).…

physics.med-ph2023

Image-Domain Material Decomposition for Dual-energy CT using Unsupervised Learning with Data-fidelity Loss

Junbo Peng, Chih-Wei Chang, Huiqiao Xie +6

Background: Dual-energy CT (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise…