267 citations · 360 across the 5 of their papers we have counts for
5 papers
Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy
Jaehee Chun, Justin C. Park, Sven Olberg +5
In this study, we propose a tailored DL framework for patient-specific performance that leverages the behavior of a model intentionally overfitted to a patient-specific training da…
Generating Synthesized Computed Tomography (CT) from Cone-Beam Computed Tomography (CBCT) using CycleGAN for Adaptive Radiation Therapy
Xiao Liang, Liyuan Chen, Dan Nguyen +5
Cone beam computed tomography (CBCT) images can be used for dose calculation in adaptive radiation therapy (ART). The main challenges are the large artefacts and inaccurate Hounsfi…
Statistical models and regularization strategies in statistical image reconstruction of low-dose X-ray CT: a survey
Hao Zhang, Jing Wang, Jianhua Ma +2
Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose X-ray computed tomography (CT) as compared to the convent…
A method for real-time volumetric imaging in radiotherapy using single x-ray projection
Yuan Xu, Hao Yan, Luo Ouyang +5
In this paper, we present a new method to generate an instantaneous volumetric image using a single x-ray projection. To fully extract motion information hidden in projection image…
A Contour-Guided Deformable Image Registration Algorithm for Adaptive Radiotherapy
Xuejun Gu, Bin Dong, Jing Wang +4
In adaptive radiotherapy, deformable image registration is often conducted between the planning CT and treatment CT (or cone beam CT) to generate a deformation vector field (DVF) f…