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 …
Sparse-view x-ray CT reconstruction via total generalized variation regularization
Sparse-view CT reconstruction algorithms via total variation (TV) optimize the data iteratively
on the basis of a noise-and artifact-reducing model, resulting in significant radiation dose …
on the basis of a noise-and artifact-reducing model, resulting in significant radiation dose …
Adaptive-weighted total variation minimization for sparse data toward low-dose x-ray computed tomography image reconstruction
Previous studies have shown that by minimizing the total variation (TV) of the to-be-
estimated image with some data and other constraints, piecewise-smooth x-ray computed …
estimated image with some data and other constraints, piecewise-smooth x-ray computed …
CaGAN: A cycle-consistent generative adversarial network with attention for low-dose CT imaging
Z Huang, Z Chen, Q Zhang, G Quan… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Although lowering X-ray radiation helps reduce the risk of cancer in patients, low-dose
computed tomography (LDCT) technology usually leads to poor image quality, such as …
computed tomography (LDCT) technology usually leads to poor image quality, such as …
Iterative image‐domain decomposition for dual‐energy CT
Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging
applications due to its capability of material decomposition. Direct decomposition via matrix …
applications due to its capability of material decomposition. Direct decomposition via matrix …
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 …
Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study
Due to the inter-and intra-variation of respiratory motion, it is highly desired to provide real-
time volumetric images during the treatment delivery of lung stereotactic body radiation …
time volumetric images during the treatment delivery of lung stereotactic body radiation …
Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone‐beam CT
Purpose: Image reconstruction and motion model estimation in four‐dimensional cone‐
beam CT (4D‐CBCT) are conventionally handled as two sequential steps. Due to the limited …
beam CT (4D‐CBCT) are conventionally handled as two sequential steps. Due to the limited …
Defect-Induced in Situ Atomic Doping in Transition Metal Dichalcogenides via Liquid-Phase Synthesis toward Efficient Electrochemical Activity
Transition metal dichalcogenides (TMDs), due to their fascinating properties, have emerged
as potential next-generation semiconducting nanomaterials across diverse fields of …
as potential next-generation semiconducting nanomaterials across diverse fields of …