[HTML][HTML] Neuroimaging in the era of artificial intelligence: current applications
R Monsour, M Dutta, AZ Mohamed… - Federal …, 2022 - ncbi.nlm.nih.gov
Background Artificial intelligence (AI) in medicine has shown significant promise, particularly
in neuroimaging. AI increases efficiency and reduces errors, making it a valuable resource …
in neuroimaging. AI increases efficiency and reduces errors, making it a valuable resource …
Ultra–Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs
Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing
diagnostic quality by using deep learning methods. Materials and Methods Forty data sets …
diagnostic quality by using deep learning methods. Materials and Methods Forty data sets …
Ultra‐low‐dose PET reconstruction using generative adversarial network with feature matching and task‐specific perceptual loss
Purpose Our goal was to use a generative adversarial network (GAN) with feature matching
and task‐specific perceptual loss to synthesize standard‐dose amyloid Positron emission …
and task‐specific perceptual loss to synthesize standard‐dose amyloid Positron emission …
Projection space implementation of deep learning–guided low-dose brain PET imaging improves performance over implementation in image space
Our purpose was to assess the performance of full-dose (FD) PET image synthesis in both
image and sinogram space from low-dose (LD) PET images and sinograms without …
image and sinogram space from low-dose (LD) PET images and sinograms without …
Low-count whole-body PET with deep learning in a multicenter and externally validated study
More widespread use of positron emission tomography (PET) imaging is limited by its high
cost and radiation dose. Reductions in PET scan time or radiotracer dosage typically …
cost and radiation dose. Reductions in PET scan time or radiotracer dosage typically …
Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models
Purpose To provide a holistic and complete comparison of the five most advanced AI models
in the augmentation of low-dose 18F-FDG PET data over the entire dose reduction …
in the augmentation of low-dose 18F-FDG PET data over the entire dose reduction …
Low-dose PET image noise reduction using deep learning: application to cardiac viability FDG imaging in patients with ischemic heart disease
CN Ladefoged, P Hasbak, C Hornnes… - Physics in Medicine …, 2021 - iopscience.iop.org
Abstract Introduction. Cardiac [18 F] FDG-PET is widely used for viability testing in patients
with chronic ischemic heart disease. Guidelines recommend injection of 200–350 MBq [18 …
with chronic ischemic heart disease. Guidelines recommend injection of 200–350 MBq [18 …
Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning
Purpose We aimed to evaluate the performance of deep learning-based generalization of
ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with …
ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with …
Clinical and phantom validation of a deep learning based denoising algorithm for F-18-FDG PET images from lower detection counting in comparison with the …
G Bonardel, A Dupont, P Decazes, M Queneau… - EJNMMI physics, 2022 - Springer
Background PET/CT image quality is directly influenced by the F-18-FDG injected activity.
The higher the injected activity, the less noise in the reconstructed images but the more …
The higher the injected activity, the less noise in the reconstructed images but the more …