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 …
Artificial intelligence-based image enhancement in pet imaging: Noise reduction and resolution enhancement
PET is a noninvasive molecular imaging modality that is increasingly popular in oncology,
neurology, cardiology, and other fields. 1–3 Accurate quantitation of PET radiotracer uptake …
neurology, cardiology, and other fields. 1–3 Accurate quantitation of PET radiotracer uptake …
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 …
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 …
Image denoising: The deep learning revolution and beyond—a survey paper
Image denoising—removal of additive white Gaussian noise from an image—is one of the
oldest and most studied problems in image processing. Extensive work over several …
oldest and most studied problems in image processing. Extensive work over several …
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 …
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 …
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 …
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 …
An investigation of quantitative accuracy for deep learning based denoising in oncological PET
Reducing radiation dose is important for PET imaging. However, reducing injection doses
causes increased image noise and low signal-to-noise ratio (SNR), subsequently affecting …
causes increased image noise and low signal-to-noise ratio (SNR), subsequently affecting …