In this study, we propose a novel deep learning-based method, which integrates histogram matching (HM) into a cycle-consistent adversarial network (CycleGAN) ...
A novel deep learning-based method, which integrates histogram matching (HM) into a cycle-consistent adversarial network ( CycleGAN) framework called ...
HM-CycleGAN, to learn a mapping between chest CBCT images and paired planning CT images obtained at simulation. Histogram matching is performed via an ...
Attenuation values in histograms of the lung and atelectasis were studied using 2 methods of calculating the atelectatic area. On the basis of the present ...
Chest CBCT-based synthetic CT using cycle-consistent adversarial network with histogram matching. In Ivana Isgum, Bennett A. Landman, editors, Medical ...
Chest CBCT-based synthetic CT using cycle-consistent adversarial network with histogram matching. R. Qiu, Y. Lei, A. Kesarwala, K. Higgins, J. Bradley, ...
Oct 29, 2021 · A deep-learning-based algorithm that corrects image artifacts in thoracic CBCT images is presented. The proposed algorithm was trained with paired planning CT- ...
Apr 24, 2023 · This study aims to utilize a hybrid approach of phantom correction and deep learning for synthesized CT (sCT) images generation based on cone-beam CT (CBCT) ...
In this study, we developed a deep-learning based approach to translate CBCT image to synthetic CT (sCT) image that preserves both CT image quality and CBCT ...
May 20, 2024 · We introduce a refined unsupervised learning model called improved vision transformer CycleGAN (IViT-CycleGAN).