Nuclear Medicine

Artificial Intelligence for PET Image Reconstruction.

Assessment of deep learning-based PET attenuation correction frameworks in the sinogram domain.

This study set out to investigate various deep learning frameworks for PET attenuation correction in...

Evaluating the Efficacy of Povidone-Iodine Solution Infection Prophylaxis in Immediate Tissue Expander-Based Breast Reconstruction: A Controlled Retrospective Analysis.

There is currently no consensus among plastic surgeons regarding the optimal infection prophylaxis ...

Development of attenuation correction methods using deep learning in brain-perfusion single-photon emission computed tomography.

PURPOSE: Computed tomography (CT)-based attenuation correction (CTAC) in single-photon emission comp...

Automated Data Quality Control in FDOPA brain PET Imaging using Deep Learning.

INTRODUCTION: With biomedical imaging research increasingly using large datasets, it becomes critica...

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.

OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic p...

A different overview of staging PET/CT images in patients with esophageal cancer: the role of textural analysis with machine learning methods.

OBJECTIVE: This study evaluates the ability of several machine learning (ML) algorithms, developed u...

Ultrasensitive biosensing platform based on luminescence quenching ability of fullerenol quantum dots.

An ultrasensitive biosensing platform for DNA and ochratoxin A (OTA) detection is constructed based ...

Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT.

To develop an artificial intelligence (AI)-based method for the detection of focal skeleton/bone mar...

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.

Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures an...

Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging.

PURPOSE: Accurate prognostic stratification of patients with oropharyngeal squamous cell carcinoma (...

Prediction of the treatment outcome using machine learning with FDG-PET image-based multiparametric approach in patients with oral cavity squamous cell carcinoma.

AIM: To investigate the value of machine learning-based multiparametric analysis using 2-[F]-fluoro-...

Machine Learning with F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction.

Coronary F-sodium fluoride (F-NaF) PET and CT angiography-based quantitative plaque analysis have sh...

Increasing the confidence of F-Florbetaben PET interpretations: Machine learning quantitative approximation.

AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study ...

Quantitative salivary gland SPECT/CT using deep convolutional neural networks.

Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m ...

Deep learning-based attenuation correction for brain PET with various radiotracers.

OBJECTIVES: Attenuation correction (AC) is crucial for ensuring the quantitative accuracy of positro...

A novel deep-learning-based approach for automatic reorientation of 3D cardiac SPECT images.

PURPOSE: Reconstructed transaxial cardiac SPECT images need to be reoriented into standard short-axi...

Quantitative Molecular Positron Emission Tomography Imaging Using Advanced Deep Learning Techniques.

The widespread availability of high-performance computing and the popularity of artificial intellige...

Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting.

PURPOSE: In this work, we addressed fully automatic determination of tumor functional uptake from po...

Multi-task weak supervision enables anatomically-resolved abnormality detection in whole-body FDG-PET/CT.

Computational decision support systems could provide clinical value in whole-body FDG-PET/CT workflo...

Emerging methods for the characterization of ischemic heart disease: ultrafast Doppler angiography, micro-CT, photon-counting CT, novel MRI and PET techniques, and artificial intelligence.

After an ischemic event, disruptive changes in the healthy myocardium may gradually develop and may ...