Radiology

Nuclear Medicine

Latest AI and machine learning research in nuclear medicine for healthcare professionals.

5,509 articles
Stay Ahead - Weekly Nuclear Medicine research updates
Subscribe
Browse Categories
Showing 778-798 of 5,509 articles
De novo Gastrinoma: A Case Report.

Gastrinomas are neuroendocrine tumors characterized by gastrin overexpression - 80% are sporadic and...

Independent brain F-FDG PET attenuation correction using a deep learning approach with Generative Adversarial Networks.

OBJECTIVE: Attenuation correction (AC) of positron emission tomography (PET) data poses a challenge ...

Effect of storage on the quality of processed palm oil collected from local milling points within Ile-Ife, Osun State, Nigeria.

The influence of storage practices on physicochemical and microbial changes in crude palm oil (CPO) ...

Ensemble of neural networks for 3D position estimation in monolithic PET detectors.

We propose an ensemble of multilayer feedforward neural networks to estimate the 3D position of phot...

Intelligent Imaging: Radiomics and Artificial Neural Networks in Heart Failure.

BACKGROUND: Our previous work with iodine meta-iodobenzylguanidine (I-mIBG) radionuclide imaging amo...

Image reconstruction for positron emission tomography based on patch-based regularization and dictionary learning.

PURPOSE: Positron emission tomography (PET) is an important tool for nuclear medical imaging. It has...

Three-dimensional convolutional neural networks for simultaneous dual-tracer PET imaging.

Dual-tracer positron emission tomography (PET) is a promising technique to measure the distribution ...

Machine learning for radiomics-based multimodality and multiparametric modeling.

Due to the recent developments of both hardware and software technologies, multimodality medical ima...

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topograp...

PET image denoising using unsupervised deep learning.

PURPOSE: Image quality of positron emission tomography (PET) is limited by various physical degradat...

Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis.

Multiple sclerosis (MS) is the most common demyelinating disease. In MS, demyelination occurs in the...

An investigation of quantitative accuracy for deep learning based denoising in oncological PET.

Reducing radiation dose is important for PET imaging. However, reducing injection doses causes incre...

Fully automated analysis for bone scintigraphy with artificial neural network: usefulness of bone scan index (BSI) in breast cancer.

OBJECTIVE: Artificial neural network (ANN) technology has been developed for clinical use to analyze...

High-Resolution SPECT Imaging of Stimuli-Responsive Soft Microrobots.

Untethered small-scale robots have great potential for biomedical applications. However, critical ba...

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

OBJECTIVE: Using CT texture analysis and machine learning methods, this study aims to distinguish th...

Flexible Prediction of CT Images From MRI Data Through Improved Neighborhood Anchored Regression for PET Attenuation Correction.

Given the complicated relationship between the magnetic resonance imaging (MRI) signals and the atte...

Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images.

Application of kinetic modeling (KM) on a voxel level in dynamic PET images frequently suffers from ...

Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

OBJECTIVE: Quantitative PET/MR imaging is challenged by the accuracy of synthetic CT (sCT) generatio...

Browse Categories