1 citations · 2 across the 5 of their papers we have counts for
5 papers
TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model
Zhenkai Zhang, Krista A. Ehinger, Tom Drummond
We introduce TCAM-Diff, a novel 3D medical image generation model that reduces the memory requirements to encode and generate high-resolution 3D data. This model utilizes a decoder…
From Sparse X-rays to 3D CT: Training-Free Reconstruction with Diffusion Priors
Zhenkai Zhang, Markus Hiller, Krista A. Ehinger +1
Solving 3D medical inverse problems typically requires training dedicated supervised models for each specific task and measurement setting. To break this dependency, we present TF-…
Pixel-Level Residual Diffusion Transformer: Scalable 3D CT Volume Generation
Zhenkai Zhang, Markus Hiller, Krista A. Ehinger +1
Generating high-resolution 3D CT volumes with fine details remains challenging due to substantial computational demands and optimization difficulties inherent to existing generativ…
Improving Denoising Diffusion Models via Simultaneous Estimation of Image and Noise
Zhenkai Zhang, Krista A. Ehinger, Tom Drummond
This paper introduces two key contributions aimed at improving the speed and quality of images generated through inverse diffusion processes. The first contribution involves repara…
Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering
Dongting Hu, Zhenkai Zhang, Tingbo Hou +3
The rendering scheme in neural radiance field (NeRF) is effective in rendering a pixel by casting a ray into the scene. However, NeRF yields blurred rendering results when the trai…