CT super-resolution GAN constrained by the identical, residual, and cycle learning ensemble (GAN-CIRCLE)
In this paper, we present a semi-supervised deep learning approach to accurately recover
high-resolution (HR) CT images from low-resolution (LR) counterparts. Specifically, with the …
high-resolution (HR) CT images from low-resolution (LR) counterparts. Specifically, with the …
Domain progressive 3D residual convolution network to improve low-dose CT imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
A novel calibration method incorporating nonlinear optimization and ball‐bearing markers for cone‐beam CT with a parameterized trajectory
Purpose Cone‐beam (CB) CT is a powerful noninvasive imaging modality, and is widely
used in many applications. Accurate geometric parameters are essential for high‐quality …
used in many applications. Accurate geometric parameters are essential for high‐quality …
Hybrid source translation scanning mode for interior tomography
S Ni, HJ Yu, J Chen, CJ Liu, FL Liu - Optics Express, 2023 - opg.optica.org
Interior tomography is a promising technique that can be used to image large objects with
high acquisition efficiency. However, it suffers from truncation artifacts and attenuation value …
high acquisition efficiency. However, it suffers from truncation artifacts and attenuation value …
A nonconvex model‐based combined geometric calibration scheme for micro cone‐beam CT with irregular trajectories
Background Many dedicated cone‐beam CT (CBCT) systems have irregular scanning
trajectories. Compared with the standard CBCT calibration, accurate calibration for CBCT …
trajectories. Compared with the standard CBCT calibration, accurate calibration for CBCT …
A novel super-resolution CT image reconstruction via semi-supervised generative adversarial network
X Jiang, M Liu, F Zhao, X Liu, H Zhou - Neural Computing and Applications, 2020 - Springer
Reconstruction of super-resolution CT images using deep learning requires a large number
of high-resolution images. However, high-resolution images are often limited to access due …
of high-resolution images. However, high-resolution images are often limited to access due …
Osnet & mneto: Two types of general reconstruction architectures for linear computed tomography in multi-scenarios
Z Wang, Z Deng, F Liu, Y Huang, H Yu, J Cui - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, linear computed tomography (LCT) systems have actively attracted attention. To
weaken projection truncation and image the region of interest (ROI) for LCT, the …
weaken projection truncation and image the region of interest (ROI) for LCT, the …
Multi source translation based projection completion for interior region of interest tomography with CBCT
C Tan, H Yu, Y Xi, L Li, M Liao, F Liu, L Duan - Optics Express, 2022 - opg.optica.org
Interior tomography by rotary computed tomography (RCT) is an effective method to improve
the detection efficiency and achieve high-resolution imaging for the region of interest (ROI) …
the detection efficiency and achieve high-resolution imaging for the region of interest (ROI) …
A Self-contained Calibration Scheme for Micro CT with Irregular Trajectories Based on Phantom Auto-measurement
Cone-beam CT (CBCT) with irregular trajectories has been widely used in various fields
such as clinical medicine and scientific research. Precise geometric calibration is a crucial …
such as clinical medicine and scientific research. Precise geometric calibration is a crucial …
PIDNET: Polar Transformation Based Implicit Disentanglement Network for Truncation Artifacts
The interior problem, a persistent ill-posed challenge in CT imaging, gives rise to truncation
artifacts capable of distorting CT values, thereby significantly impacting clinical diagnoses …
artifacts capable of distorting CT values, thereby significantly impacting clinical diagnoses …