AIMC Topic: Positron-Emission Tomography

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Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging.

European journal of nuclear medicine and molecular imaging
PURPOSE: Tendency is to moderate the injected activity and/or reduce acquisition time in PET examinations to minimize potential radiation hazards and increase patient comfort. This work aims to assess the performance of regular full-dose (FD) synthes...

Modeling autosomal dominant Alzheimer's disease with machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.

4D deep image prior: dynamic PET image denoising using an unsupervised four-dimensional branch convolutional neural network.

Physics in medicine and biology
Although convolutional neural networks (CNNs) demonstrate the superior performance in denoising positron emission tomography (PET) images, a supervised training of the CNN requires a pair of large, high-quality PET image datasets. As an unsupervised ...

A deep learning framework for F-FDG PET imaging diagnosis in pediatric patients with temporal lobe epilepsy.

European journal of nuclear medicine and molecular imaging
PURPOSE: Epilepsy is one of the most disabling neurological disorders, which affects all age groups and often results in severe consequences. Since misdiagnoses are common, many pediatric patients fail to receive the correct treatment. Recently, F-fl...

True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation.

European journal of nuclear medicine and molecular imaging
PURPOSE: While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement u...

Improved amyloid burden quantification with nonspecific estimates using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we p...

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.

BMC bioinformatics
BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and ...

Detection of transient neurotransmitter response using personalized neural networks.

Physics in medicine and biology
Measurement of stimulus-induced dopamine release and other types of transient neurotransmitter response (TNR) from dynamic positron emission tomography (PET) images typically suffers from limited detection sensitivity and high false positive (FP) rat...

A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.

Physics in medicine and biology
An important need exists for reliable positron emission tomography (PET) tumor-segmentation methods for tasks such as PET-based radiation-therapy planning and reliable quantification of volumetric and radiomic features. To address this need, we propo...

Artificial intelligence applications for oncological positron emission tomography imaging.

European journal of radiology
Positron emission tomography (PET), a functional and dynamic molecular imaging technique, is generally used to reveal tumors' biological behavior. Radiomics allows a high-throughput extraction of multiple features from images with artificial intellig...