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Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase F-Florbetaben PET and clinical features.
Scientific reports
Jul 1, 2025
This study developed machine learning models to predict Aβ positivity in Alzheimer's disease by integrating early-phase F-Florbetaben PET and clinical data to improve diagnostic accuracy. Furthermore, the study explored machine learning models to pre...
A support vector machine-based approach to guide the selection of a pseudo-reference region for brain PET quantification.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Oct 13, 2024
A Support Vector Machine (SVM) based approach was developed to identify a pseudo-reference region for brain PET scans with the aim of reducing interscan and intersubject variability. By training a binary linear SVM classifier with PET datasets from t...
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images.
Journal of imaging informatics in medicine
Oct 2, 2024
Medical image classification using convolutional neural networks (CNNs) is promising but often requires extensive manual tuning for optimal model definition. Neural architecture search (NAS) automates this process, reducing human intervention signifi...
Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.
Biosensors & bioelectronics
Jun 13, 2024
The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...
A deep learning model for generating [F]FDG PET Images from early-phase [F]Florbetapir and [F]Flutemetamol PET images.
European journal of nuclear medicine and molecular imaging
Jun 11, 2024
INTRODUCTION: Amyloid-β (Aβ) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunct...
Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.
Biomedical engineering online
Dec 20, 2022
BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta...
Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.
PloS one
Oct 20, 2021
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...
Generation of synthetic PET images of synaptic density and amyloid from F-FDG images using deep learning.
Medical physics
Jul 27, 2021
PURPOSE: Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isoto...
Increasing the confidence of F-Florbetaben PET interpretations: Machine learning quantitative approximation.
Revista espanola de medicina nuclear e imagen molecular
Apr 21, 2021
AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study the patterns of F-Florbetaben brain deposition.
Translating amyloid PET of different radiotracers by a deep generative model for interchangeability.
NeuroImage
Feb 19, 2021
It is challenging to compare amyloid PET images obtained with different radiotracers. Here, we introduce a new approach to improve the interchangeability of amyloid PET acquired with different radiotracers through image-level translation. Deep genera...
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