Nuclear Medicine

Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.

To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A receptors (5-HT2AR) show a particularly profound age-related decline and are also reduced in neurodegenerative disorders, such as Alzheimer's disease. ...

FPGA-based fast bin-ratio spiking ensemble network for radioisotope identification.

In this work, we demonstrate the training, conversion, and implementation flow of an FPGA-based bin-ratio ensemble spiking neural network applied for radioisotope identification. The combination of techniques including learned step quantisation (LSQ) and pruning facilitated the implementation by compressing the network's parameters down to 30% yet retaining the accuracy of 97.04% with an accuracy ...

Prognostic value of a novel artificial intelligence-based coronary CTA-derived ischemia algorithm among patients with normal or abnormal myocardial perfusion.

BACKGROUND: Among patients with obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CTA), downstream positron emiss...

Fast SPECT/CT planar bone imaging enabled by deep learning enhancement.

BACKGROUND: The application of deep learning methods in rapid bone scintigraphy is increasingly promising for minimizing the duration of SPECT examina...

How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households.

Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the hom...

Union is strength: the combination of radiomics features and 3D-deep learning in a sole model increases diagnostic accuracy in demented patients: a whole brain 18FDG PET-CT analysis.

OBJECTIVE: FDG PET imaging plays a crucial role in the evaluation of demented patients by assessing regional cerebral glucose metabolism. In recent ye...

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve ...

A serial image analysis architecture with positron emission tomography using machine learning combined for the detection of lung cancer.

INTRODUCTION AND OBJECTIVES: Lung cancer is the second type of cancer with the second highest incidence rate and the first with the highest mortality ...

The application of different machine learning models based on PET/CT images and EGFR in predicting brain metastasis of adenocarcinoma of the lung.

OBJECTIVE: To explore the value of six machine learning models based on PET/CT radiomics combined with EGFR in predicting brain metastases of lung ade...

Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence.

The evolution of Positron Emission Tomography (PET), culminating in the Total-Body PET (TB-PET) system, represents a paradigm shift in medical imaging...

A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features.

BACKGROUND: Positron emission tomography (PET) is extensively employed for diagnosing and staging various tumors, including liver cancer, lung cancer,...

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated ...

Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method.

Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interactio...

[Involvement of essential trace elements in the pathogenesis of thyroid diseases: diagnostic markers and analytical methods for determination].

AIM: To study the role of iodine, selenium and zinc in the pathogenesis of iodine deficiency and autoimmune thyroid diseases and scientifically substa...

Extended pelvic lymph node dissection in robot-assisted radical prostatectomy is an independent risk factor for major complications.

The aim of this study is to evaluate the major postoperative complication rate after robot-assisted radical prostatectomy (RARP) and to identify relat...

Machine learning-based analysis of Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.

Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes. Since the tissue sampling procedures are invasive...

Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) or positron emission tomography (PET), is one of t...

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convo...

Machine learning approach using F-FDG-PET-radiomic features and the visibility of right ventricle F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment F-FDG-PET-based radiomic features for predicting adverse ...

Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [F]FDG PET/CT predicts survival in multiple myeloma.

PURPOSE: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [F]FDG PET/CT can provide prognostic informa...