AIMC Topic: Positron-Emission Tomography
Clear Filters Showing 391 to 400 of 503 articles
Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.
Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
Oct 2, 2017
OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flo...
Deep reconstruction model for dynamic PET images.
PloS one
Sep 21, 2017
Accurate and robust tomographic reconstruction from dynamic positron emission tomography (PET) acquired data is a difficult problem. Conventional methods, such as the maximum likelihood expectation maximization (MLEM) algorithm for reconstructing the...
AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: Defining a summary measure.
NeuroImage
Jul 26, 2017
Utilizing [18F]-AV-1451 tau positron emission tomography (PET) as an Alzheimer disease (AD) biomarker will require identification of brain regions that are most important in detecting elevated tau pathology in preclinical AD. Here, we utilized an uns...
Multi-modal discriminative dictionary learning for Alzheimer's disease and mild cognitive impairment.
Computer methods and programs in biomedicine
Jul 18, 2017
BACKGROUND AND OBJECTIVE: The differentiation of mild cognitive impairment (MCI), which is the prodromal stage of Alzheimer's disease (AD), from normal control (NC) is important as the recent research emphasis on early pre-clinical stage for possible...
Identifying incipient dementia individuals using machine learning and amyloid imaging.
Neurobiology of aging
Jul 11, 2017
Identifying individuals destined to develop Alzheimer's dementia within time frames acceptable for clinical trials constitutes an important challenge to design studies to test emerging disease-modifying therapies. Although amyloid-β protein is the co...
Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.
Physics in medicine and biology
Apr 5, 2017
A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated ...
A Novel Fusion Framework Based on Adaptive PCNN in NSCT Domain for Whole-Body PET and CT Images.
Computational and mathematical methods in medicine
Apr 3, 2017
The PET and CT fusion images, combining the anatomical and functional information, have important clinical meaning. This paper proposes a novel fusion framework based on adaptive pulse-coupled neural networks (PCNNs) in nonsubsampled contourlet trans...
Early identification of mild cognitive impairment using incomplete random forest-robust support vector machine and FDG-PET imaging.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 7, 2017
Alzheimer's disease (AD) is the most common type of dementia and will be an increasing health problem in society as the population ages. Mild cognitive impairment (MCI) is considered to be a prodromal stage of AD. The ability to identify subjects wit...
Phantom Validation of Tc-99m Absolute Quantification in a SPECT/CT Commercial Device.
Computational and mathematical methods in medicine
Dec 14, 2016
. Similar to PET, absolute quantitative imaging is becoming available in commercial SPECT/CT devices. This study's goal was to assess quantitative accuracy of activity recovery as a function of image reconstruction parameters and count statistics in ...
Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Oct 2, 2016
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...
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