101 citations · 313 across the 10 of their papers we have counts for
10 papers
2D antiscatter grid and scatter sampling based CBCT pipeline for image guided radiation therapy
Farhang Bayat, Dan Ruan, Moyed Miften +1
Poor tissue visualization and quantitative accuracy in CBCT is a major barrier in expanding the role of CBCT imaging from target localization to quantitative treatment monitoring a…
An Efficient and Robust Method for Chest X-Ray Rib Suppression that Improves Pulmonary Abnormality Diagnosis
Di Xu, Qifan Xu, Kevin Nhieu +2
Suppression of thoracic bone shadows on chest X-rays (CXRs) has been indicated to improve the diagnosis of pulmonary disease. Previous approaches can be categorized as unsupervised…
To what extent can Plug-and-Play methods outperform neural networks alone in low-dose CT reconstruction
Qifan Xu, Qihui Lyu, Dan Ruan +1
The Plug-and-Play (PnP) framework was recently introduced for low-dose CT reconstruction to leverage the interpretability and the flexibility of model-based methods to incorporate…
An automatic deep learning-based workflow for glioblastoma survival prediction using pre-operative multimodal MR images
Jie Fu, Kamal Singhrao, Xinran Zhong +5
We proposed a fully automatic workflow for glioblastoma (GBM) survival prediction using deep learning (DL) methods. 285 glioma (210 GBM, 75 low-grade glioma) patients were included…
Fully Automated Multi-Organ Segmentation in Abdominal Magnetic Resonance Imaging with Deep Neural Networks
Yuhua Chen, Dan Ruan, Jiayu Xiao +6
Segmentation of multiple organs-at-risk (OARs) is essential for radiation therapy treatment planning and other clinical applications. We developed an Automated deep Learning-based…
Generation of abdominal synthetic CTs from 0.35T MR images using generative adversarial networks for MR-only liver radiotherapy
Jie Fu, Kamal Singhrao, Minsong Cao +7
Electron density maps must be accurately estimated to achieve valid dose calculation in MR-only radiotherapy. The goal of this study is to assess whether two deep learning models,…