Radiology

Nuclear Medicine

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

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Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images.

Positron emission tomography (PET) is a functional imaging modality widely used in neuroscience stud...

Thread/paper- and paper-based microfluidic devices for glucose assays employing artificial neural networks.

This paper describes the fabrication of and data collection from two microfluidic devices: a microfl...

Adaptive template generation for amyloid PET using a deep learning approach.

Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheim...

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which ...

Enhancing the Image Quality via Transferred Deep Residual Learning of Coarse PET Sinograms.

Increasing the image quality of positron emission tomography (PET) is an essential topic in the PET ...

Pharmacokinetics of Iodine and Fluoride following Application of an Anticaries Varnish in Adults.

Researchers have suggested that combining topical fluoride with an antiseptic to reduce cariogenic b...

Radiomics - the value of the numbers in present and future radiology.

Radiomics is a new concept that has been functioning in medicine for only a few years. This idea, cr...

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death ...

Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

OBJECTIVES: The study evaluated the automatic prediction of obstructive disease from myocardial perf...

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen p...

Improving the Accuracy of Simultaneously Reconstructed Activity and Attenuation Maps Using Deep Learning.

Simultaneous reconstruction of activity and attenuation using the maximum-likelihood reconstruction ...

Using convolutional neural networks to estimate time-of-flight from PET detector waveforms.

Although there have been impressive strides in detector development for time-of-flight positron emis...

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia....

Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods.

The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM)....

Quantitative pulmonary blood flow measurement using O-HO PET with and without tissue fraction correction: a comparison study.

BACKGROUND: Physiological measures per lung parenchyma, rather than per lung volume, sometimes refle...

Interpretation criteria for FDG PET/CT in multiple myeloma (IMPeTUs): final results. IMPeTUs (Italian myeloma criteria for PET USe).

UNLABELLED: á…Ÿ: FDG PET/CT (F-fluoro-deoxy-glucose positron emission tomography/computed tomography) ...

How Well Does Dual-energy CT with Fast Kilovoltage Switching Quantify CT Number and Iodine and Calcium Concentrations?

RATIONALE AND OBJECTIVES: Because it is imperative for understanding the performance of dual-energy ...

Ga PSMA-11 PET with CT urography protocol in the initial staging and biochemical relapse of prostate cancer.

BACKGROUND: Ga-labelled prostate specific membrane antigen (PSMA) ligand PET/CT is a promising modal...

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