A review on medical imaging synthesis using deep learning and its clinical applications
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …
clinical application. Specifically, we summarized the recent developments of deep learning …
Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …
medicine. This paper reviews applications of machine learning for the study of attenuation …
Image domain dual material decomposition for dual‐energy CT using butterfly network
W Zhang, H Zhang, L Wang, X Wang, X Hu… - Medical …, 2019 - Wiley Online Library
Purpose Dual‐energy CT (DECT) has been increasingly used in imaging applications
because of its capability for material differentiation. However, material decomposition suffers …
because of its capability for material differentiation. However, material decomposition suffers …
Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy
Low-dose computed tomography (CT) is desirable for treatment planning and simulation in
radiation therapy. Multiple rescanning and replanning during the treatment course with a …
radiation therapy. Multiple rescanning and replanning during the treatment course with a …
Iterative material decomposition for spectral CT using self-supervised Noise2Noise prior
Compared to conventional computed tomography (CT), spectral CT can provide the
capability of material decomposition, which can be used in many clinical diagnosis …
capability of material decomposition, which can be used in many clinical diagnosis …
A material decomposition method for dual‐energy CT via dual interactive Wasserstein generative adversarial networks
Z Shi, H Li, Q Cao, Z Wang, M Cheng - Medical physics, 2021 - Wiley Online Library
Purpose Dual‐energy computed tomography (DECT) is highly promising for material
characterization and identification, whereas reconstructed material‐specific images are …
characterization and identification, whereas reconstructed material‐specific images are …
Spectral CT image-domain material decomposition via sparsity residual prior and dictionary learning
T Zhang, H Yu, Y Xi, S Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The spectral computed tomography (CT) system based on a photon-counting detector (PCD)
can quantitatively analyze the material composition of the inspected object by material …
can quantitatively analyze the material composition of the inspected object by material …
Image-domain material decomposition for spectral CT using a generalized dictionary learning
The spectral computed tomography (CT) has huge advantages by providing accurate
material information. Unfortunately, due to the instability or overdetermination of the material …
material information. Unfortunately, due to the instability or overdetermination of the material …
Statistical image‐domain multimaterial decomposition for dual‐energy CT
Y Xue, R Ruan, X Hu, Y Kuang, J Wang… - Medical …, 2017 - Wiley Online Library
Purpose Dual‐energy CT (DECT) enhances tissue characterization because of its basis
material decomposition capability. In addition to conventional two‐material decomposition …
material decomposition capability. In addition to conventional two‐material decomposition …
Generalized deep iterative reconstruction for sparse-view CT imaging
Sparse-view CT is a promising approach for reducing the x-ray radiation dose in clinical CT
imaging. However, the CT images reconstructed from the conventional filtered …
imaging. However, the CT images reconstructed from the conventional filtered …