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 …
Vision 20/20: magnetic resonance imaging‐guided attenuation correction in PET/MRI: challenges, solutions, and opportunities
Attenuation correction is an essential component of the long chain of data correction techniques
required to achieve the full potential of quantitative positron emission tomography (PET) …
required to achieve the full potential of quantitative positron emission tomography (PET) …
Joint estimation of activity and attenuation in whole-body TOF PET/MRI using constrained Gaussian mixture models
A Mehranian, H Zaidi - IEEE transactions on medical imaging, 2015 - ieeexplore.ieee.org
It has recently been shown that the attenuation map can be estimated from time-of-flight (TOF)
PET emission data using joint maximum likelihood reconstruction of attenuation and …
PET emission data using joint maximum likelihood reconstruction of attenuation and …
X-ray CT Metal Artifact Reduction Using Wavelet Domain Sparse Regularization
X-ray computed tomography (CT) imaging of patients with metallic implants usually suffers
from streaking metal artifacts. In this paper, we propose a new projection completion metal …
from streaking metal artifacts. In this paper, we propose a new projection completion metal …
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, the …
of Poisson noise, and if shorter acquisition times or reduced injected doses are used, the …
PET image reconstruction using multi-parametric anato-functional priors
A Mehranian, MA Belzunce, F Niccolini… - Physics in Medicine …, 2017 - iopscience.iop.org
In this study, we investigate the application of multi-parametric anato-functional (MR-PET)
priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address …
priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address …
Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI
Purpose In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly
challenged by the need of deriving accurate attenuation maps from MR images. A number …
challenged by the need of deriving accurate attenuation maps from MR images. A number …
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 …
(MAP) positron emission tomography (PET) image reconstruction. The MAP …
Impact of time-of-flight PET on quantification errors in MR imaging–based attenuation correction
A Mehranian, H Zaidi - Journal of Nuclear Medicine, 2015 - Soc Nuclear Med
Time-of-flight (TOF) PET/MR imaging is an emerging imaging technology with great capabilities
offered by TOF to improve image quality and lesion detectability. We assessed, for the …
offered by TOF to improve image quality and lesion detectability. We assessed, for the …
[HTML][HTML] Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise
A Mehranian, SD Wollenweber, MD Walker… - European journal of …, 2022 - Springer
Purpose To enhance the image quality of oncology [ 18 F]-FDG PET scans acquired in shorter
times and reconstructed by faster algorithms using deep neural networks. Methods List-…
times and reconstructed by faster algorithms using deep neural networks. Methods List-…