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 …
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 …
200x low-dose PET reconstruction using deep learning
Positron emission tomography (PET) is widely used in various clinical applications,
including cancer diagnosis, heart disease and neuro disorders. The use of radioactive tracer …
including cancer diagnosis, heart disease and neuro disorders. The use of radioactive tracer …
Image reconstruction using UNET-transformer network for fast and low-dose PET scans
Introduction Low-dose and fast PET imaging (low-count PET) play a significant role in
enhancing patient safety, healthcare efficiency, and patient comfort during medical imaging …
enhancing patient safety, healthcare efficiency, and patient comfort during medical imaging …
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 …
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 …
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 …
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 …
[HTML][HTML] High-quality PET image synthesis from ultra-low-dose PET/MRI using bi-task deep learning
Background Lowering the dose for positron emission tomography (PET) imaging reduces
patients' radiation burden but decreases the image quality by increasing noise and reducing …
patients' radiation burden but decreases the image quality by increasing noise and reducing …
PET image reconstruction using a cascading back-projection neural network
Positron emission tomography (PET) imaging is a noninvasive technique that makes it
possible to probe biological metabolic processes in vivo. However, PET image …
possible to probe biological metabolic processes in vivo. However, PET image …