3 citations · 4 across the 3 of their papers we have counts for
3 papers
When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT
Matt Y. Cheung, Sophia Zorek, Tucker J. Netherton +4
Diffusion models demonstrate state-of-the-art performance on image generation, and are gaining traction for sparse medical image reconstruction tasks. However, compared to classica…
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image Segmentation
McKell Woodland, Nihil Patel, Austin Castelo +13
Clinically deployed deep learning-based segmentation models are known to fail on data outside of their training distributions. While clinicians review the segmentations, these mode…
Automated WBRT Treatment Planning via Deep Learning Auto-Contouring and Customizable Landmark-Based Field Aperture Design
Yao Xiao, Carlos Cardenas, Dong Joo Rhee +12
In this work, we developed and evaluated a novel pipeline consisting of two landmark-based field aperture generation approaches for WBRT treatment planning; they are fully automate…