AIMC Topic: Positron-Emission Tomography
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Partial-ring PET image restoration using a deep learning based method.
Physics in medicine and biology
Nov 21, 2019
PET scanners with partial-ring geometry have been proposed for various imaging purposes. The incomplete projection data obtained from this design cause undesirable artifacts in the reconstructed images. In this study, we investigated the performance ...
Predicting O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Nov 13, 2019
To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neural network (dCNN) was trained to combine single- and multi-delay arterial spin labeling (ASL) and structural images to predict gold-standard O-water ...
Oxygen Radioisotopes
Adolescent
Water
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Models, Biological
Positron-Emission Tomography
Cerebrovascular Circulation
Young Adult
Adult
Male
Middle Aged
Brain
Female
Reproducibility of Results
Aged
Humans
Neural Networks, Computer
Data Analysis
Algorithms
A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.
NeuroImage
Nov 1, 2019
Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algo...
Texture analysis and multiple-instance learning for the classification of malignant lymphomas.
Computer methods and programs in biomedicine
Oct 23, 2019
BACKGROUND AND OBJECTIVES: Malignant lymphomas are cancers of the immune system and are characterized by enlarged lymph nodes that typically spread across many different sites. Many different histological subtypes exist, whose diagnosis is typically ...
An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders.
BMC bioinformatics
Oct 11, 2019
BACKGROUND: The analysis of health and medical data is crucial for improving the diagnosis precision, treatments and prevention. In this field, machine learning techniques play a key role. However, the amount of health data acquired from digital mach...
Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.
PloS one
Oct 7, 2019
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived....
Ensemble of neural networks for 3D position estimation in monolithic PET detectors.
Physics in medicine and biology
Oct 4, 2019
We propose an ensemble of multilayer feedforward neural networks to estimate the 3D position of photoelectric interactions in monolithic detectors. The ensemble is trained with data generated from optical Monte Carlo simulations only. The originality...
Image reconstruction for positron emission tomography based on patch-based regularization and dictionary learning.
Medical physics
Sep 20, 2019
PURPOSE: Positron emission tomography (PET) is an important tool for nuclear medical imaging. It has been widely used in clinical diagnosis, scientific research, and drug testing. PET is a kind of emission computed tomography. Its basic imaging princ...
Three-dimensional convolutional neural networks for simultaneous dual-tracer PET imaging.
Physics in medicine and biology
Sep 19, 2019
Dual-tracer positron emission tomography (PET) is a promising technique to measure the distribution of two tracers in the body by a single scan, which can improve the clinical accuracy of disease diagnosis and can also serve as a research tool for sc...
Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.
Human brain mapping
Sep 10, 2019
F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). ...
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