AIMC Topic: Positron-Emission Tomography
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Deep learning generation of preclinical positron emission tomography (PET) images from low-count PET with task-based performance assessment.
Medical physics
May 6, 2024
BACKGROUND: Preclinical low-count positron emission tomography (LC-PET) imaging offers numerous advantages such as facilitating imaging logistics, enabling longitudinal studies of long- and short-lived isotopes as well as increasing scanner throughpu...
Prognostic value of combining clinical factors, F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.
Annals of nuclear medicine
May 5, 2024
OBJECTIVE: To investigate the prognostic value of F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma...
Prostate-specific Membrane Antigen: Interpretation Criteria, Standardized Reporting, and the Use of Machine Learning.
PET clinics
May 4, 2024
Prostate-specific membrane antigen targeting positron emission tomography (PSMA-PET) is routinely used for the staging and restaging of patients with various stages of prostate cancer. For clear communication with referring physicians and to improve ...
PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI.
La Radiologia medica
May 3, 2024
PURPOSE: High PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and th...
Impact of F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 1, 2024
We aimed to investigate the effects of F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. We extracted 1,037 F-FDG PET radiomic features q...
Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.
GeroScience
Apr 26, 2024
To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A r...
Prognostic value of a novel artificial intelligence-based coronary CTA-derived ischemia algorithm among patients with normal or abnormal myocardial perfusion.
Journal of cardiovascular computed tomography
Apr 24, 2024
BACKGROUND: Among patients with obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CTA), downstream positron emission tomography (PET) perfusion imaging can be performed to assess the presence of myocardial ischemi...
Myocardial Perfusion Imaging
Finland
Angina, Unstable
Coronary Stenosis
Adenosine
Coronary Vessels
Artificial Intelligence
Vasodilator Agents
Predictive Value of Tests
Algorithms
Computed Tomography Angiography
Prognosis
Coronary Circulation
Male
Coronary Angiography
Retrospective Studies
Middle Aged
Coronary Artery Disease
Female
Severity of Illness Index
Positron-Emission Tomography
Reproducibility of Results
Time Factors
Risk Factors
Humans
Aged
Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.
Medical image analysis
Apr 17, 2024
The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of K images by utilizing deep learning techniques to reduce th...
Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence.
Cancer imaging : the official publication of the International Cancer Imaging Society
Apr 11, 2024
The evolution of Positron Emission Tomography (PET), culminating in the Total-Body PET (TB-PET) system, represents a paradigm shift in medical imaging. This paper explores the transformative role of Artificial Intelligence (AI) in enhancing clinical ...
A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features.
Computers in biology and medicine
Apr 9, 2024
BACKGROUND: Positron emission tomography (PET) is extensively employed for diagnosing and staging various tumors, including liver cancer, lung cancer, and lymphoma. Accurate subtype classification of tumors plays a crucial role in formulating effecti...
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