Nuclear Medicine

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 studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as magnetic resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we pre...

Multicenter validation of [F]-FDG PET and support-vector machine discriminant analysis in automatically classifying patients with amyotrophic lateral sclerosis versus controls.

OBJECTIVE: F-Fluorodeoxyglucose (F-FDG) positron emission tomography (PET) single-center studies using support vector machine (SVM) approach to differentiate amyotrophic lateral sclerosis (ALS) from controls have shown high overall accuracy on an individual patient basis using local a priori defined classifiers. The aim of the study was to validate the SVM accuracy on a multicentric level.

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 microfluidic thread/paper based analytical device (μTPAD)...

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

Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anato...

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 is likely to be very useful for diagnosis of AD an...

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 community. For instance, thin-pixelated crystals h...

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 bacteria may be more effective than fluoride applic...

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, created recently, relies on processing innumerable q...

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human ther...

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 based on adenosine myocardial perfusion SPECT (MPS...

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 perfusion imaging (MPI) by deep learning as compared w...

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 prodromal mild cognitive impairment (MCI) phase whe...

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

Simultaneous reconstruction of activity and attenuation using the maximum-likelihood reconstruction of activity and attenuation (MLAA) augmented by ti...

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. Currently, no treatment exists to slow down or st...

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). Ga-Pentixafor PET/CT can capture the abnormal mol...

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [I]FP-CIT SPECT images.

PURPOSE: This work aimed to assess the potential of a set of features extracted from [I]FP-CIT SPECT brain images to be used in the computer-aided "in...

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 reflect the disease status. PET images of the lung, whi...

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

UNLABELLED: ᅟ: FDG PET/CT (F-fluoro-deoxy-glucose positron emission tomography/computed tomography) is a useful tool to image multiple myeloma (MM). H...

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 computed tomography scanner to determine clinical ...

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 modality in primary staging (PS) and biochemical relaps...