PET image denoising using unsupervised deep learning
Purpose Image quality of positron emission tomography (PET) is limited by various physical
degradation factors. Our study aims to perform PET image denoising by utilizing prior …
degradation factors. Our study aims to perform PET image denoising by utilizing prior …
PET image denoising using a deep neural network through fine tuning
Positron emission tomography (PET) is a functional imaging modality widely used in clinical
diagnosis. In this paper, we trained a deep convolutional neural network to improve PET …
diagnosis. In this paper, we trained a deep convolutional neural network to improve PET …
Dynamic PET image denoising using deep image prior combined with regularization by denoising
H Sun, L Peng, H Zhang, Y He, S Cao, L Lu - IEEE Access, 2021 - ieeexplore.ieee.org
The quantitative accuracy of positron emission tomography (PET) is affected by several
factors, including the intrinsic resolution of the imaging system and inherently noisy data …
factors, including the intrinsic resolution of the imaging system and inherently noisy data …
Noise2Void: unsupervised denoising of PET images
Objective: Elevated noise levels in positron emission tomography (PET) images lower image
quality and quantitative accuracy and are a confounding factor for clinical interpretation. The …
quality and quantitative accuracy and are a confounding factor for clinical interpretation. The …
4D deep image prior: dynamic PET image denoising using an unsupervised four-dimensional branch convolutional neural network
F Hashimoto, H Ohba, K Ote, A Kakimoto… - Physics in Medicine …, 2021 - iopscience.iop.org
Although convolutional neural networks (CNNs) demonstrate the superior performance in
denoising positron emission tomography (PET) images, a supervised training of the CNN …
denoising positron emission tomography (PET) images, a supervised training of the CNN …
PET image denoising based on denoising diffusion probabilistic model
Purpose Due to various physical degradation factors and limited counts received, PET
image quality needs further improvements. The denoising diffusion probabilistic model …
image quality needs further improvements. The denoising diffusion probabilistic model …
Dynamic PET image denoising using deep convolutional neural networks without prior training datasets
Deep learning has attracted growing interest for application to medical imaging, such as
positron emission tomography (PET), due to its excellent performance. Convolutional neural …
positron emission tomography (PET), due to its excellent performance. Convolutional neural …
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 …
Supervised learning with cyclegan for low-dose FDG PET image denoising
PET imaging involves radiotracer injections, raising concerns about the risk of radiation
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …
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 …