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 …
Review and prospect: artificial intelligence in advanced medical imaging
Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …
imaging. Recently, deep learning-based AI techniques have been actively investigated in …
Iterative PET image reconstruction using convolutional neural network representation
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and
limited number of detected photons. Recently, the deep neural networks have been widely …
limited number of detected photons. Recently, the deep neural networks have been widely …
Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement
Image processing plays a crucial role in maximising diagnostic quality of positron emission
tomography (PET) images. Recently, deep learning methods developed across many fields …
tomography (PET) images. Recently, deep learning methods developed across many fields …
Direct patlak reconstruction from dynamic PET data using the kernel method with MRI information based on structural similarity
Positron emission tomography (PET) is a functional imaging modality widely used in
oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor …
oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor …
From simultaneous to synergistic MR‐PET brain imaging: A review of hybrid MR‐PET imaging methodologies
Abstract Simultaneous Magnetic Resonance Imaging (MRI) and Positron Emission
Tomography (PET) scanning is a recent major development in biomedical imaging. The full …
Tomography (PET) scanning is a recent major development in biomedical imaging. The full …
Deep generalized learning model for PET image reconstruction
Low-count positron emission tomography (PET) imaging is challenging because of the ill-
posedness of this inverse problem. Previous studies have demonstrated that deep learning …
posedness of this inverse problem. Previous studies have demonstrated that deep learning …
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 …
MR-guided kernel EM reconstruction for reduced dose PET imaging
J Bland, A Mehranian, MA Belzunce… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Positron emission tomography (PET) image reconstruction is highly susceptible to the
impact of Poisson noise, and if shorter acquisition times or reduced injected doses are used …
impact of Poisson noise, and if shorter acquisition times or reduced injected doses are used …
Artificial neural network enhanced Bayesian PET image reconstruction
B Yang, L Ying, J Tang - IEEE transactions on medical imaging, 2018 - ieeexplore.ieee.org
In positron emission tomography (PET) image reconstruction, the Bayesian framework with
various regularization terms has been implemented to constrain the radio tracer distribution …
various regularization terms has been implemented to constrain the radio tracer distribution …