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 …
Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space
Positron emission tomography/computed tomography (PET/CT) is increasingly used in
oncology, neurology, cardiology, and emerging medical fields. The success stems from the …
oncology, neurology, cardiology, and emerging medical fields. The success stems from the …
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 …
A deep neural network for parametric image reconstruction on a large axial field-of-view PET
Y Li, J Hu, H Sari, S Xue, R Ma, S Kandarpa… - European journal of …, 2023 - Springer
Purpose The PET scanners with long axial field of view (AFOV) having~ 20 times higher
sensitivity than conventional scanners provide new opportunities for enhanced parametric …
sensitivity than conventional scanners provide new opportunities for enhanced parametric …
Artificial intelligence for PET and SPECT image enhancement
Nuclear medicine imaging modalities such as PET and SPECT are confounded by high
noise levels and low spatial resolution, necessitating postreconstruction image …
noise levels and low spatial resolution, necessitating postreconstruction image …
Deep learning-based PET image denoising and reconstruction: a review
This review focuses on positron emission tomography (PET) imaging algorithms and traces
the evolution of PET image reconstruction methods. First, we provide an overview of …
the evolution of PET image reconstruction methods. First, we provide an overview of …
Unsupervised PET logan parametric image estimation using conditional deep image prior
Recently, deep learning-based denoising methods have been gradually used for PET
images denoising and have shown great achievements. Among these methods, one …
images denoising and have shown great achievements. Among these methods, one …
Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm
Objective. Deep image prior (DIP) has recently attracted attention owing to its unsupervised
positron emission tomography (PET) image reconstruction method, which does not require …
positron emission tomography (PET) image reconstruction method, which does not require …
An educated warm start for deep image prior-based micro CT reconstruction
Deep image prior (DIP) was recently introduced as an effective unsupervised approach for
image restoration tasks. DIP represents the image to be recovered as the output of a deep …
image restoration tasks. DIP represents the image to be recovered as the output of a deep …
Self-supervised pre-training for deep image prior-based robust pet image denoising
Deep image prior (DIP) has been successfully applied to positron emission tomography
(PET) image restoration, enabling represent implicit prior using only convolutional neural …
(PET) image restoration, enabling represent implicit prior using only convolutional neural …