[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 …
Deep learning for PET image reconstruction
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
MD-Recon-Net: a parallel dual-domain convolutional neural network for compressed sensing MRI
Compressed sensing magnetic resonance imaging (CS-MRI) is a theoretical framework that
can accurately reconstruct images from undersampled k-space data with a much lower …
can accurately reconstruct images from undersampled k-space data with a much lower …
Model-based deep learning PET image reconstruction using forward–backward splitting expectation–maximization
A Mehranian, AJ Reader - IEEE transactions on radiation and …, 2020 - ieeexplore.ieee.org
We propose a forward-backward splitting algorithm to integrate deep learning into maximum-
a-posteriori (MAP) positron emission tomography (PET) image reconstruction. The MAP …
a-posteriori (MAP) positron emission tomography (PET) image reconstruction. The MAP …
DPIR-Net: Direct PET image reconstruction based on the Wasserstein generative adversarial network
Positron emission tomography (PET) is an advanced medical imaging technique widely
used in various clinical applications, such as tumor detection and neurologic disorders …
used in various clinical applications, such as tumor detection and neurologic disorders …
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 …
[HTML][HTML] Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network
In the last two decades, it has been shown that anatomically-guided PET reconstruction can
lead to improved bias-noise characteristics in brain PET imaging. However, despite …
lead to improved bias-noise characteristics in brain PET imaging. However, despite …
True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation
Purpose While sampled or short-frame realizations have shown the potential power of deep
learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose …
learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose …
High temporal-resolution dynamic PET image reconstruction using a new spatiotemporal kernel method
G Wang - IEEE transactions on medical imaging, 2018 - ieeexplore.ieee.org
Current clinical dynamic PET has an effective temporal resolution of 5-10 seconds, which
can be adequate for traditional compartmental modeling but is inadequate for exploiting the …
can be adequate for traditional compartmental modeling but is inadequate for exploiting the …
Generative Adversarial Network–Enhanced Ultra-Low-Dose [18F]-PI-2620 τ PET/MRI in Aging and Neurodegenerative Populations
BACKGROUND AND PURPOSE: With the utility of hybrid τ PET/MR imaging in the
screening, diagnosis, and follow-up of individuals with neurodegenerative diseases, we …
screening, diagnosis, and follow-up of individuals with neurodegenerative diseases, we …