[HTML][HTML] The promise of artificial intelligence and deep learning in PET and SPECT imaging
This review sets out to discuss the foremost applications of artificial intelligence (AI),
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …
Efficient artificial intelligence approaches for medical image processing in healthcare: comprehensive review, taxonomy, and analysis
OAMF Alnaggar, BN Jagadale, MAN Saif… - Artificial Intelligence …, 2024 - Springer
In healthcare, medical practitioners employ various imaging techniques such as CT, X-ray,
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme
P Bing, W Liu, Z Zhai, J Li, Z Guo, Y **ang… - Frontiers in …, 2024 - frontiersin.org
Background Electrocardiogram (ECG) signals are inevitably contaminated with various
kinds of noises during acquisition and transmission. The presence of noises may produce …
kinds of noises during acquisition and transmission. The presence of noises may produce …
Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
Purpose This work was set out to investigate the feasibility of dose reduction in SPECT
myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning …
myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning …
[HTML][HTML] DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms
Purpose Reducing the injected activity and/or the scanning time is a desirable goal to
minimize radiation exposure and maximize patients' comfort. To achieve this goal, we …
minimize radiation exposure and maximize patients' comfort. To achieve this goal, we …
Deep learning-based synthetic CT generation from MR images: comparison of generative adversarial and residual neural networks
Currently, MRI-only radiotherapy (RT) eliminates some of the concerns about using CT
images in RT chains such as the registration of MR images to a separate CT, extra dose …
images in RT chains such as the registration of MR images to a separate CT, extra dose …
Anatomical-guided attention enhances unsupervised PET image denoising performance
Although supervised convolutional neural networks (CNNs) often outperform conventional
alternatives for denoising positron emission tomography (PET) images, they require many …
alternatives for denoising positron emission tomography (PET) images, they require many …
A personalized deep learning denoising strategy for low-count PET images
Objective. Deep learning denoising networks are typically trained with images that are
representative of the testing data. Due to the large variability of the noise levels in positron …
representative of the testing data. Due to the large variability of the noise levels in positron …
Self-supervised deep learning for joint 3D low-dose PET/CT image denoising
Deep learning (DL)-based denoising of low-dose positron emission tomography (LDPET)
and low-dose computed tomography (LDCT) has been widely explored. However, previous …
and low-dose computed tomography (LDCT) has been widely explored. However, previous …
Deep learning-assisted PET imaging achieves fast scan/low-dose examination
Y **ng, W Qiao, T Wang, Y Wang, C Li, Y Lv, C **… - EJNMMI physics, 2022 - Springer
Purpose This study aimed to investigate the impact of a deep learning (DL)-based denoising
method on the image quality and lesion detectability of 18F-FDG positron emission …
method on the image quality and lesion detectability of 18F-FDG positron emission …