Radiology

Nuclear Medicine

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

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Circulating tumor DNA for monitoring classic Hodgkin lymphoma patients: Correlation with FDG-PET/CT.

The value of circulating tumor DNA (ctDNA) as a biomarker of disease activity in classic Hodgkin lym...

Recent Advances and Challenges in Enzymatic Depolymerization and Recycling of PET Wastes.

Poly (ethylene terephthalate) (PET) is one of the most commonly used plastics in daily life and vari...

Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions.

Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conve...

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell...

Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain.

BACKGROUND: Low-dose positron emission tomography (LD-PET) imaging is commonly employed in preclinic...

Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.

OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coro...

The Progressive Veterinary Practice.

Veterinary practices must be forward-thinking to effectively serve today's pet owners and move into ...

Predictive value and potential association of PET/CT radiomics on lymph node metastasis of cervical cancer.

OBJECTIVE: Due to the information-rich nature of positron emission tomography/computed tomography (P...

Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects.

The integration of positron emission tomography (PET) and single-photon emission computed tomography...

Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning.

PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-inv...

Low PSA radiographic disease progression on C11-choline PET.

BACKGROUND: For men with prostate cancer, radiographic progression may occur without a concordant ri...

Image Denoising of Low-Dose PET Mouse Scans with Deep Learning: Validation Study for Preclinical Imaging Applicability.

PURPOSE: Positron emission tomography (PET) image quality can be improved by higher injected activit...

Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space.

Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurolog...

Deep learning based diagnosis of Alzheimer's disease using FDG-PET images.

PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease ...

Machine learning methods for tracer kinetic modelling.

Tracer kinetic modelling based on dynamic PET is an important field of Nuclear Medicine for quantita...

Advancements in Positron Emission Tomography Detectors: From Silicon Photomultiplier Technology to Artificial Intelligence Applications.

This review article focuses on PET detector technology, which is the most crucial factor in determin...

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios.

Deep neural networks (DNNs) have already impacted the field of medicine in data analysis, classifica...

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT.

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accu...

A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging.

Dynamic PET imaging provides superior physiological information than conventional static PET imaging...

Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters.

PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clini...

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