AIMC Topic: Positron-Emission Tomography
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Position estimation using neural networks in semi-monolithic PET detectors.
Physics in medicine and biology
Dec 9, 2022
. The goal of this work is to experimentally compare the 3D spatial and energy resolution of a semi-monolithic detector suitable for total-body positron emission tomography (TB-PET) scanners using different surface crystal treatments and silicon phot...
Deep learning-based dynamic PET parametric K image generation from lung static PET.
European radiology
Nov 18, 2022
OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric K provides better quantification and improve speci...
Posterior estimation using deep learning: a simulation study of compartmental modeling in dynamic positron emission tomography.
Medical physics
Nov 18, 2022
BACKGROUND: In medical imaging, images are usually treated as deterministic, while their uncertainties are largely underexplored.
Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.
Physical and engineering sciences in medicine
Nov 10, 2022
The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modality of brain imaging to detect multiple stages of dementia, including Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI)...
NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.
European radiology experimental
Nov 8, 2022
NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses....
Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.
BioMed research international
Oct 11, 2022
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...
Applying deep learning attenuation correction in the presence of motion.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Oct 7, 2022
Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.
Nature communications
Oct 6, 2022
Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation and scatter correction for CT-free PET imaging, a critical bottleneck is their limited capability in handling large heterogeneity of tracers and scanne...
Development of a deep learning network for Alzheimer's disease classification with evaluation of imaging modality and longitudinal data.
Physics in medicine and biology
Sep 30, 2022
. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer's disease (AD), there remains a clear clinical need for reliable tools to extract diagnoses from neuroimages. Significant work has been done to develop deep le...
Breast PET/MRI Hybrid Imaging and Targeted Tracers.
Journal of magnetic resonance imaging : JMRI
Sep 27, 2022
The recent introduction of hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) as a promising imaging modality for breast cancer assessment has prompted fervent research activity on its clinical applications. The current knowledg...
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