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Showing 1366-1386 of 5,219 articles

Swarming behavior and in vivo monitoring of enzymatic nanomotors within the bladder.

Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their abilit...

Mar 2021 34043548

PET/CT for Brain Amyloid: A Feasibility Study for Scan Time Reduction by Deep Learning.

PURPOSE: This study was to develop a convolutional neural network (CNN) model with a residual learni...

Mar 2021 33512838

Study of the Usefulness of Bone Scan Index Calculated From 99m-Technetium- Hydroxymethylene Diphosphonate (Tc-HMDP) Bone Scintigraphy for Bone Metastases from Prostate Cancer Using Deep Learning Algorithms.

BACKGROUND: BSI calculated from bone scintigraphy using technetium-methylene diphosphonate (Tc-MDP) ...

Jan 2021 32484112

Deep learning for intelligent diagnosis in thyroid scintigraphy.

OBJECTIVE: To construct deep learning (DL) models to improve the accuracy and efficiency of thyroid ...

Jan 2021 33445994

Blinded Clinical Evaluation for Dementia of Alzheimer's Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods.

BACKGROUND: Advanced machine learning methods can aid in the identification of dementia risk using n...

Jan 2021 33579858

[Accuracy of Classification of Cerebral Blood Flow Reduction Patterns Using Statistical Analysis Images Generated with Simulated SPECT Datasets via Deep Learning].

PURPOSE: The aim of this study was to evaluate the classification accuracy of specific blood flow re...

Jan 2021 34148900

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer.

FDG PET/CT imaging is commonly used in diagnosis and follow-up of metastatic breast cancer, but its ...

Jul 2020 33018283

Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images.

Semi-automatic measurements are performed on FDG PET-CT images to monitor the evolution of metastati...

Jul 2020 33018284

Machine Learning Methods for Optimal Radiomics-Based Differentiation Between Recurrence and Inflammation: Application to Nasopharyngeal Carcinoma Post-therapy PET/CT Images.

PURPOSE: To identify optimal machine learning methods for radiomics-based differentiation of local r...

Jun 2020 31338709

Diagnostic classification of solitary pulmonary nodules using support vector machine model based on 2-[18F]fluoro-2-deoxy-D-glucose PET/computed tomography texture features.

PURPOSE: This study aimed to evaluate the diagnostic value of a support vector machine (SVM) model b...

Jun 2020 32282636

The Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Score.

PURPOSE: The aim of this study was to evaluate random forests (RFs) to identify ROIs on F-florbetapi...

Jun 2020 32366785

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

BACKGROUND: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for m...

Jan 2020 31884486

[Generation of the Pseudo CT Image Based on the Deep Learning Technique Aimed for the Attenuation Correction of the PET Image].

Computed tomography (CT) is used for the attenuation correction (AC) of [F-18] fluoro-deoxy-glucose ...

Jan 2020 33229845

Thyrotropin receptor antibody immunoassays may not be reliable in confirming diagnosis of Painless Thyroiditis.

BACKGROUND: Scintigraphy using 99mTc-pertechnetate (TS) is the diagnostic test to differentiate thyr...

Jan 2020 34084251

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

PURPOSE: Quantitative analysis of dopamine transporter (DAT) single-photon emission computed tomogra...

Dec 2019 30847821

A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.

PURPOSE: We sought to distinguish lung adenocarcinoma (ADC) from squamous cell carcinoma using a mac...

Dec 2019 31689276

Diagnostic accuracy of single-source dual-energy computed tomography and ultrasonography for detection of lateral cervical lymph node metastases of papillary thyroid carcinoma.

BACKGROUND: Dual-energy computed tomography (DECT) imaging can generate iodine-based material decomp...

Dec 2019 32030219

Radiology

Browse Categories

Swarming behavior and in vivo monitoring of enzymatic nanomotors within the bladder.

PET/CT for Brain Amyloid: A Feasibility Study for Scan Time Reduction by Deep Learning.

Study of the Usefulness of Bone Scan Index Calculated From 99m-Technetium- Hydroxymethylene Diphosphonate (Tc-HMDP) Bone Scintigraphy for Bone Metastases from Prostate Cancer Using Deep Learning Algorithms.

Deep learning for intelligent diagnosis in thyroid scintigraphy.

Blinded Clinical Evaluation for Dementia of Alzheimer's Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods.

[Accuracy of Classification of Cerebral Blood Flow Reduction Patterns Using Statistical Analysis Images Generated with Simulated SPECT Datasets via Deep Learning].

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer.

Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images.

Machine Learning Methods for Optimal Radiomics-Based Differentiation Between Recurrence and Inflammation: Application to Nasopharyngeal Carcinoma Post-therapy PET/CT Images.

Diagnostic classification of solitary pulmonary nodules using support vector machine model based on 2-[18F]fluoro-2-deoxy-D-glucose PET/computed tomography texture features.

The Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Score.

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

[Generation of the Pseudo CT Image Based on the Deep Learning Technique Aimed for the Attenuation Correction of the PET Image].

Thyrotropin receptor antibody immunoassays may not be reliable in confirming diagnosis of Painless Thyroiditis.

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.

Diagnostic accuracy of single-source dual-energy computed tomography and ultrasonography for detection of lateral cervical lymph node metastases of papillary thyroid carcinoma.

[A Case of Disseminated Carcinomatosis of the Bone Marrow Developing 15 Months after Gastrectomy].

[A Case of Splenic Lymph Node Metastasis from the Distal Bile Duct Carcinoma Seven Years after a Curative Resection].

Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

The Use of Random Forests to Classify Amyloid Brain PET.

Browse Categories