10 citations · 10 across the 3 of their papers we have counts for
3 papers
Efficient Noise Context-Aware Representation for Low-Dose CT Denoising
Minwoo Yu, N. Robert Bennett, Jongduk Baek +1
While deep learning-based denoising has become widely adopted in low-dose CT, conventional models use generic architectures designed for natural images, failing to account for non-…
Single-Shot Quantitative X-ray Imaging Using a Primary Modulator and Dual-Layer Detector
Linxi Shi, N. Robert Bennett, Alexander Vezeridis +2
Purpose: Conventional x-ray imaging and fluoroscopy have limitations in quantitation due to several challenges, including scatter, beam hardening, and overlapping tissues. In this…
Deep Learning-Based Reconstruction of Interventional Tools from Four X-Ray Projections for Tomographic Interventional Guidance
Elias Eulig, Joscha Maier, Michael Knaup +4
Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a C-arm system. However, the projective data provide only limited in…