A review on deep learning approaches for low-dose computed tomography restoration
Computed Tomography (CT) is a widely use medical image modality in clinical medicine,
because it produces excellent visualizations of fine structural details of the human body. In …
because it produces excellent visualizations of fine structural details of the human body. In …
Noise suppression with similarity-based self-supervised deep learning
Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and
photon-counting computed tomography (CT) denoising can optimize diagnostic …
photon-counting computed tomography (CT) denoising can optimize diagnostic …
A review on self-adaptation approaches and techniques in medical image denoising algorithms
Noise is a definite degeneration of medical images that interferes with the diagnostic
process in clinical medicine. Although many denoising algorithms have been developed to …
process in clinical medicine. Although many denoising algorithms have been developed to …
One model to unite them all: Personalized federated learning of multi-contrast MRI synthesis
Curation of large, diverse MRI datasets via multi-institutional collaborations can help
improve learning of generalizable synthesis models that reliably translate source-onto target …
improve learning of generalizable synthesis models that reliably translate source-onto target …
A novel denoising method for low-dose CT images based on transformer and CNN
J Zhang, Z Shangguan, W Gong, Y Cheng - Computers in Biology and …, 2023 - Elsevier
Computed Tomography (CT) has become a mainstream imaging tool in medical diagnosis.
However, the issue of increased cancer risk due to radiation exposure has raised public …
However, the issue of increased cancer risk due to radiation exposure has raised public …
AIGAN: Attention–encoding Integrated Generative Adversarial Network for the reconstruction of low-dose CT and low-dose PET images
X-ray computed tomography (CT) and positron emission tomography (PET) are two of the
most commonly used medical imaging technologies for the evaluation of many diseases …
most commonly used medical imaging technologies for the evaluation of many diseases …
[HTML][HTML] SYNAPSE: An international roadmap to large brain imaging
APJ Stampfl, Z Liu, J Hu, K Sawada, H Takano… - Physics Reports, 2023 - Elsevier
Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
collaborating in a major project called “SYNAPSE”(Synchrotrons for Neuroscience: an Asia …
ISCL: Interdependent self-cooperative learning for unpaired image denoising
With the advent of advances in self-supervised learning, paired clean-noisy data are no
longer required in deep learning-based image denoising. However, existing blind denoising …
longer required in deep learning-based image denoising. However, existing blind denoising …
Training low dose CT denoising network without high quality reference data
J Jing, W Xia, M Hou, H Chen, Y Liu… - Physics in Medicine & …, 2022 - iopscience.iop.org
Objective. Currently, the field of low-dose CT (LDCT) denoising is dominated by supervised
learning based methods, which need perfectly registered pairs of LDCT and its …
learning based methods, which need perfectly registered pairs of LDCT and its …
Constrained predictive filters for single image bokeh rendering
Bokeh rendering is a technique used to take pictures with out-of-focus areas to highlight
regions of interest. Due to limitations in hardware and shooting condition, rendering a bokeh …
regions of interest. Due to limitations in hardware and shooting condition, rendering a bokeh …