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Showing 841-861 of 5,509 articles

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using F-FDG PET of the Brain.

Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzhe...

Nov 2018 PMID: 30398430

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

OBJECTIVES: We evaluated whether machine learning may be helpful for the detection of lung cancer in...

Nov 2018 PMID: 30527183

Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.

In this article, the authors aim to maximally utilize multimodality neuroimaging and genetic data fo...

Nov 2018 PMID: 30381863

F-FDG PET/CT-Guided Real-Time Automated Robotic Arm-Assisted Needle Navigation for Percutaneous Biopsy of Hypermetabolic Bone Lesions: Diagnostic Performance and Clinical Impact.

OBJECTIVE: The purpose of this study is to establish the feasibility, safety, diagnostic performance...

Nov 2018 PMID: 30383406

Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT.

AIM: To develop an algorithm, based on convolutional neural network (CNN), for the classification of...

Oct 2018 PMID: 30510492

Translation of morphological and functional musculoskeletal imaging.

In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void tha...

Oct 2018 PMID: 30273968

Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study.

PURPOSE: In this study, we proposed an automated deep learning (DL) method for head and neck cancer ...

Oct 2018 PMID: 30473644

Learning SPECT detector angular response function with neural network for accelerating Monte-Carlo simulations.

A method to speed up [Formula: see text] simulations of single photon emission computed tomography (...

Oct 2018 PMID: 30238925

Accuracy of an artificial neural network for detecting a regional abnormality in myocardial perfusion SPECT.

OBJECTIVES: The patient-based diagnosis with an artificial neural network (ANN) has shown potential ...

Oct 2018 PMID: 30302633

Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG-PET/CT in Hodgkin and non-Hodgkin lymphomas.

BACKGROUND: 18F-FDG-PET/CT has become a standard for assessing treatment response in patients with l...

Oct 2018 PMID: 30284376

Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.

Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on...

Sep 2018 PMID: 30262516

Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.

OBJECTIVES: To describe and validate an artificial intelligence (AI)-driven structured reporting sys...

Sep 2018 PMID: 30209754

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation.

PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited n...

Sep 2018 PMID: 30222554

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging I...

Sep 2018 PMID: 30185806

Diagnostic performance of real-time robotic arm-assisted F-FDG PET/CT-guided percutaneous biopsy in metabolically active abdominal and pelvic lesions.

PURPOSE: To evaluate the feasibility and diagnostic performance of F-FDG PET/CT-guided biopsy of abd...

Aug 2018 PMID: 30167803

Synthesis of Patient-Specific Transmission Data for PET Attenuation Correction for PET/MRI Neuroimaging Using a Convolutional Neural Network.

Attenuation correction is a notable challenge associated with simultaneous PET/MRI, particularly in ...

Aug 2018 PMID: 30166355

Radiology

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A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using F-FDG PET of the Brain.

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.

F-FDG PET/CT-Guided Real-Time Automated Robotic Arm-Assisted Needle Navigation for Percutaneous Biopsy of Hypermetabolic Bone Lesions: Diagnostic Performance and Clinical Impact.

Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT.

Translation of morphological and functional musculoskeletal imaging.

Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study.

Learning SPECT detector angular response function with neural network for accelerating Monte-Carlo simulations.

Accuracy of an artificial neural network for detecting a regional abnormality in myocardial perfusion SPECT.

Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG-PET/CT in Hodgkin and non-Hodgkin lymphomas.

Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.

Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation.

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Diagnostic performance of real-time robotic arm-assisted F-FDG PET/CT-guided percutaneous biopsy in metabolically active abdominal and pelvic lesions.

Synthesis of Patient-Specific Transmission Data for PET Attenuation Correction for PET/MRI Neuroimaging Using a Convolutional Neural Network.

Dixon-VIBE Deep Learning (DIVIDE) Pseudo-CT Synthesis for Pelvis PET/MR Attenuation Correction.

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?

Multilevel Feature Representation of FDG-PET Brain Images for Diagnosing Alzheimer's Disease.

Quantitative susceptibility mapping using deep neural network: QSMnet.

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