13 citations · 46 across the 20 of their papers we have counts for
4 papers · 1 filter
Unsupervised Training of a Dynamic Context-Aware Deep Denoising Framework for Low-Dose Fluoroscopic Imaging
Sun-Young Jeon, Sen Wang, Adam S. Wang +2
Fluoroscopy is critical for real-time X-ray visualization in medical imaging. However, low-dose images are compromised by noise, potentially affecting diagnostic accuracy. Noise re…
PFCM: Poisson flow consistency models for low-dose CT image denoising
Dennis Hein, Grant Stevens, Adam Wang +1
X-ray computed tomography (CT) is widely used for medical diagnosis and treatment planning; however, concerns about ionizing radiation exposure drive efforts to optimize image qual…
Window-Level is a Strong Denoising Surrogate
Ayaan Haque, Adam Wang, Abdullah-Al-Zubaer Imran
CT image quality is heavily reliant on radiation dose, which causes a trade-off between radiation dose and image quality that affects the subsequent image-based diagnostic performa…
Assessing Robustness to Noise: Low-Cost Head CT Triage
Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren +4
Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems w…