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 …
Penalized PET reconstruction using deep learning prior and local linear fitting
Motivated by the great potential of deep learning in medical imaging, we propose an
iterative positron emission tomography reconstruction framework using a deep learning …
iterative positron emission tomography reconstruction framework using a deep learning …
PET image reconstruction using deep image prior
Recently, deep neural networks have been widely and successfully applied in computer
vision tasks and have attracted growing interest in medical imaging. One barrier for the …
vision tasks and have attracted growing interest in medical imaging. One barrier for the …
DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem
The purpose of this research was to implement a deep learning network to overcome two of
the major bottlenecks in improved image reconstruction for clinical positron emission …
the major bottlenecks in improved image reconstruction for clinical positron emission …
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 …
Generative adversarial network based regularized image reconstruction for PET
Positron emission tomography (PET) is an ill-posed inverse problem and suffers high noise
due to limited number of detected events. Prior information can be used to improve the …
due to limited number of detected events. Prior information can be used to improve the …
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 …
Higher SNR PET image prediction using a deep learning model and MRI image
PET images often suffer poor signal-to-noise ratio (SNR). Our objective is to improve the
SNR of PET images using a deep neural network (DNN) model and MRI images without …
SNR of PET images using a deep neural network (DNN) model and MRI images without …
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 …
Full‐count PET recovery from low‐count image using a dilated convolutional neural network
K Spuhler, M Serrano‐Sosa, R Cattell… - Medical …, 2020 - Wiley Online Library
Purpose Positron emission tomography (PET) is an essential technique in many clinical
applications that allows for quantitative imaging at the molecular level. This study aims to …
applications that allows for quantitative imaging at the molecular level. This study aims to …