AIMC Topic: Positron-Emission Tomography
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Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images.
BMC cancer
Aug 6, 2021
BACKGROUND: This study aimed to assess the utility of deep learning analysis using pretreatment FDG-PET images to predict local treatment outcome in oropharyngeal squamous cell carcinoma (OPSCC) patients.
Aged, 80 and over
Adult
Biomarkers, Tumor
Female
Aged
ROC Curve
Image Processing, Computer-Assisted
Treatment Outcome
Male
Middle Aged
Deep Learning
Humans
Prognosis
Clinical Decision-Making
Positron-Emission Tomography
Disease Management
Fluorodeoxyglucose F18
Kaplan-Meier Estimate
Oropharyngeal Neoplasms
Neoplasm Staging
Workflow
Combined Modality Therapy
Squamous Cell Carcinoma of Head and Neck
Positron Emission Tomography Computed Tomography
Anatomy and Physiology of Artificial Intelligence in PET Imaging.
PET clinics
Aug 5, 2021
Artificial intelligence (AI) has seen an explosion in interest within nuclear medicine. This interest is driven by the rapid progress and eye-catching achievements of machine learning algorithms. The growing foothold of AI in molecular imaging is exp...
Artificial Intelligence-Based Data Corrections for Attenuation and Scatter in Position Emission Tomography and Single-Photon Emission Computed Tomography.
PET clinics
Aug 5, 2021
Recent developments in artificial intelligence (AI) technology have enabled new developments that can improve attenuation and scatter correction in PET and single-photon emission computed tomography (SPECT). These technologies will enable the use of ...
Artificial Intelligence in PET: An Industry Perspective.
PET clinics
Aug 3, 2021
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has the ability to enhance and optimize all aspects of the PET imaging chai...
Total-Body PET Kinetic Modeling and Potential Opportunities Using Deep Learning.
PET clinics
Aug 3, 2021
The uEXPLORER total-body PET/CT system provides a very high level of detection sensitivity and simultaneous coverage of the entire body for dynamic imaging for quantification of tracer kinetics. This article describes the fundamentals and potential b...
A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET.
European journal of nuclear medicine and molecular imaging
Jul 30, 2021
PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-...
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...
Evaluation of Deep Learning-Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jul 22, 2021
Attenuation correction remains a challenge in pelvic PET/MRI. In addition to the segmentation/model-based approaches, deep learning methods have shown promise in synthesizing accurate pelvic attenuation maps (μ-maps). However, these methods often mis...
Populational and individual information based PET image denoising using conditional unsupervised learning.
Physics in medicine and biology
Jul 19, 2021
Our study aims to improve the signal-to-noise ratio of positron emission tomography (PET) imaging using conditional unsupervised learning. The proposed method does not require low- and high-quality pairs for network training which can be easily appli...
Deep residual-convolutional neural networks for event positioning in a monolithic annular PET scanner.
Physics in medicine and biology
Jul 12, 2021
PET scanners based on monolithic pieces of scintillator can potentially produce superior performance characteristics (high spatial resolution and detection sensitivity, for example) compared to conventional PET scanners. Consequently, we initiated de...
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