Attenuation Correction for Amyloid PET Imaging Using Deep Learning Based on 3D UTE/Multi-Echo Dixon MR images
111 Objectives: The cortical uptake of amyloid PET imaging is a powerful biomarker for the
diagnosis and treatment monitoring of Alzheimer's disease (AD). As the cortical regions are …
diagnosis and treatment monitoring of Alzheimer's disease (AD). As the cortical regions are …
Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging
Purpose PET measures of amyloid and tau pathologies are powerful biomarkers for the
diagnosis and monitoring of Alzheimer's disease (AD). Because cortical regions are close to …
diagnosis and monitoring of Alzheimer's disease (AD). Because cortical regions are close to …
Improvement in quantitative amyloid imaging using ZTE-based attenuation correction in PET/MRI
645 Objectives: Accurate quantification of uptake in dementia patients using amyloid tracers
is important in making the clinical diagnosis as well as for clinical trials. We aimed to …
is important in making the clinical diagnosis as well as for clinical trials. We aimed to …
Long-term test-retest repeatability of PET/MR attenuation correction in longitudinal amyloid brain imaging: impact of software and hardware upgrades
P1093 Introduction: Longitudinal amyloid PET imaging has been widely used to assess
disease progression or therapeutic responses in neurodegenerative diseases. It has been …
disease progression or therapeutic responses in neurodegenerative diseases. It has been …
Quantitative Assessment of Deep Learning-enhanced Actual Ultra-low-dose Amyloid PET/MR Imaging
521 Objectives: Combining deep learning-based methods such as convolutional neural
networks (CNNs) with the advantage of complementary information from simultaneous …
networks (CNNs) with the advantage of complementary information from simultaneous …
Fast and accurate spatial normalization of amyloid PET images without MRI using deep neural networks
SK Kang, D Kim, H Choi, JS Lee - 2021 - Soc Nuclear Med
1403 Objectives: Accurate spatial normalization (SN) of amyloid PET images for Alzheimer's
disease assessment without co-registered anatomical magnetic resonance imaging (MRI) of …
disease assessment without co-registered anatomical magnetic resonance imaging (MRI) of …
PET/CT for brain amyloid: a feasibility study for scan time reduction by deep learning
S Lee, JH Jung, D Kim, HK Lim, MA Park… - Clinical nuclear …, 2021 - journals.lww.com
Purpose This study was to develop a convolutional neural network (CNN) model with a
residual learning framework to predict the full-time 18 F-florbetaben (18 F-FBB) PET/CT …
residual learning framework to predict the full-time 18 F-florbetaben (18 F-FBB) PET/CT …
[HTML][HTML] Accurate transmission-less attenuation correction method for amyloid-β brain PET using deep neural network
The lack of physically measured attenuation maps (μ-maps) for attenuation and scatter
correction is an important technical challenge in brain-dedicated stand-alone positron …
correction is an important technical challenge in brain-dedicated stand-alone positron …
Amyloid PET quantification via end-to-end training of a deep learning
Purpose Although quantification of amyloid positron emission tomography (PET) is important
for evaluating patients with cognitive impairment, its routine clinical use is hampered by …
for evaluating patients with cognitive impairment, its routine clinical use is hampered by …
True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation
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 …
learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose …