AIMC Topic: Positron-Emission Tomography
Clear Filters Showing 431 to 440 of 503 articles
Neural Networks and Chemical Messengers: Insights into Tobacco Addiction.
Brain topography
May 13, 2025
This study investigates changes in resting-state networks (RSNs) associated with tobacco addiction (TA) and whether these changes reflect alterations in neurotransmitter systems. A total of 90 patients with TA and 46 healthy controls (HCs) matched fo...
Initial Experience With Low-Dose 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging With Deep Learning Enhancement.
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: To demonstrate the utility of deep learning enhancement (DLE) to achieve diagnostic quality low-dose positron emission tomography (PET)/magnetic resonance (MR) imaging.
Innovations in artificial intelligence for pet/mr imaging: Application and performance analysis.
Journal of X-ray science and technology
May 1, 2025
BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and MR components and radiation exposure associated with the PET modality. Artificial intelligence (AI)-based techniques offer a promising approach to ov...
Evaluating prostate cancer diagnostic methods: The role and relevance of digital rectal examination in modern era.
Investigative and clinical urology
May 1, 2025
This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements like prostate-specific antigen (PSA) testing, Prostate Health Index (PHI), magnetic resonance imaging ...
Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical data.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Feb 1, 2025
INTRODUCTION: Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, but its routine clinical use is limited by cost and accessibility barriers.
Residual Neural Networks for the Prediction of the Regularization Parameters in PET Reconstruction.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Positron Emission Tomography (PET) is a medical imaging modality relying on numerical methods that integrate the statistical properties of the measurements and prior assumptions about the images. In order to maximize the computed image quality, PET r...
PET Myocardial Flow Reserve Estimation from 4D-Coronary-CT using Deep Neural Network.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The myocardial flow reserve (MFR) index proves to be a highly effective means of assessing the severity of myocardial ischemic disease. An MFR value below two commonly indicates impaired coronary artery perfusion function. Nevertheless, the measureme...
AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.
Radiology
Jun 1, 2024
Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To dev...
In vivo neuropil density from anatomical MRI and machine learning.
Cerebral cortex (New York, N.Y. : 1991)
May 2, 2024
Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from ...
[Changes in FDG-PET Images of Small Lung and Liver Masses Caused by the Deep Learning-based Time-of-flight Processing].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2024
PURPOSE: The deep learning time-of-flight (DL-ToF) aims to replicate the ToF effects through post-processing, applying deep learning-based enhancement to PET images. This study evaluates the effectiveness of DL-ToF using a chest-abdomen phantom that ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31137
- Neural Networks, Computer 29769
- Algorithms 26908
- Deep Learning 26418
- Artificial Intelligence 24354
- Robotics 13322
- Image Processing, Computer-Assisted 9552
- Retrospective Studies 9136
- Magnetic Resonance Imaging 6198
- Reproducibility of Results 5602
- Tomography, X-Ray Computed 4778
- Support Vector Machine 4695
- Computational Biology 4246
- Brain 4056
- Computer Simulation 3887
Recent Journals
- Scientific reports 6082
- Sensors (Basel, Switzerland) 4794
- PloS one 4044
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1868
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1137
- Journal of chemical information and modeling 1006
- Nature communications 959
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 862
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 829