Quantification of amyloid PET for future clinical use: a state-of-the-art review
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's
disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be …
disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be …
A review of deep-learning-based approaches for attenuation correction in positron emission tomography
JS Lee - IEEE Transactions on Radiation and Plasma Medical …, 2020 - ieeexplore.ieee.org
Attenuation correction (AC) is essential for the generation of artifact-free and quantitatively
accurate positron emission tomography (PET) images. PET AC based on computed …
accurate positron emission tomography (PET) images. PET AC based on computed …
The use of artificial neural networks to diagnose Alzheimer's disease from brain images
Since Alzheimer's disease (AD) occurs in multiple stages of cognitive impairment, its early
diagnosis can be helpful in the process of treatment. Its early diagnosis is thus drawn the …
diagnosis can be helpful in the process of treatment. Its early diagnosis is thus drawn the …
AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning
Background Visual assessment of amyloid PET scans relies on the availability of radiologist
expertise, whereas quantification of amyloid burden typically involves MRI for processing …
expertise, whereas quantification of amyloid burden typically involves MRI for processing …
Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach
Purpose Since accurate lung cancer segmentation is required to determine the functional
volume of a tumor in [18F] FDG PET/CT, we propose a two-stage U-Net architecture to …
volume of a tumor in [18F] FDG PET/CT, we propose a two-stage U-Net architecture to …
Generative AI unlocks PET insights: brain amyloid dynamics and quantification
MN Bossa, AG Nakshathri, AD Berenguer… - Frontiers in Aging …, 2024 - frontiersin.org
Introduction Studying the spatiotemporal patterns of amyloid accumulation in the brain over
time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography …
time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography …
Prediction of post-stroke cognitive impairment using brain FDG PET: deep learning-based approach
R Lee, H Choi, KY Park, JM Kim, JW Seok - European Journal of Nuclear …, 2022 - Springer
Purpose Post-stroke cognitive impairment can affect up to one third of stroke survivors. Since
cognitive function greatly contributes to patients' quality of life, an objective quantitative …
cognitive function greatly contributes to patients' quality of life, an objective quantitative …
Visual interpretation of [18F]Florbetaben PET supported by deep learning–based estimation of amyloid burden
Purpose Amyloid PET which has been widely used for noninvasive assessment of cortical
amyloid burden is visually interpreted in the clinical setting. As a fast and easy-to-use visual …
amyloid burden is visually interpreted in the clinical setting. As a fast and easy-to-use visual …
Experimental evaluation of convolutional neural network-based inter-crystal scattering recovery for high-resolution PET detectors
S Lee, JS Lee - Physics in Medicine & Biology, 2023 - iopscience.iop.org
Objective. One major limiting factor for achieving high resolution of positron emission
tomography (PET) is a Compton scattering of the photon within the crystal, also known as …
tomography (PET) is a Compton scattering of the photon within the crystal, also known as …
Deep-learning-based cardiac amyloidosis classification from early acquired pet images
The objective of the present work was to evaluate the potential of deep learning tools for
characterizing the presence of cardiac amyloidosis from early acquired PET images, ie 15 …
characterizing the presence of cardiac amyloidosis from early acquired PET images, ie 15 …