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 …
A review of harmonization strategies for quantitative PET
G Akamatsu, Y Tsutsui, H Daisaki, K Mitsumoto… - Annals of Nuclear …, 2023 - Springer
PET can reveal in vivo biological processes at the molecular level. PET-derived quantitative
values have been used as a surrogate marker for clinical decision-making in numerous …
values have been used as a surrogate marker for clinical decision-making in numerous …
List-mode PET image reconstruction using deep image prior
List-mode positron emission tomography (PET) image reconstruction is an important tool for
PET scanners with many lines-of-response and additional information such as time-of-flight …
PET scanners with many lines-of-response and additional information such as time-of-flight …
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 …
Evaluation of the performance of a high-resolution time-of-flight PET system dedicated to the head and breast according to NEMA NU 2-2012 standard
D Morimoto-Ishikawa, K Hanaoka, S Watanabe… - EJNMMI physics, 2022 - Springer
Background This study evaluated the physical performance of a positron emission
tomography (PET) system dedicated to the head and breast according to the National …
tomography (PET) system dedicated to the head and breast according to the National …
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 …
ReconU-Net: a direct PET image reconstruction using U-Net architecture with back projection-induced skip connection
F Hashimoto, K Ote - Physics in Medicine & Biology, 2024 - iopscience.iop.org
Objective. This study aims to introduce a novel back projection-induced U-Net-shaped
architecture, called ReconU-Net, based on the original U-Net architecture for deep learning …
architecture, called ReconU-Net, based on the original U-Net architecture for deep learning …
The quest for multifunctional and dedicated PET instrumentation with irregular geometries
We focus on reviewing state-of-the-art developments of dedicated PET scanners with
irregular geometries and the potential of different aspects of multifunctional PET imaging …
irregular geometries and the potential of different aspects of multifunctional PET imaging …
Markerless head motion tracking and event-by-event correction in brain PET
Objective. Head motion correction (MC) is an essential process in brain positron emission
tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based …
tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based …
Whole reconstruction-free system design for direct positron emission imaging from image generation to attenuation correction
Direct positron emission imaging (dPEI), which does not require a mathematical
reconstruction step, is a next-generation molecular imaging modality. To maximize the …
reconstruction step, is a next-generation molecular imaging modality. To maximize the …