Radiology

Nuclear Medicine

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

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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe ...

Iodine Density of Lymphoma, Metastatic SCCA, and Normal Cervical lymph nodes: A Comparative Analysis Based on DLSCT.

OBJECTIVE: To compare iodine density (ID) and contrast-enhanced attenuation value (CEAV) from dual-l...

Nutrient based classification of Phyllospora comosa biomasses using machine learning algorithms: Towards sustainable valorisation.

Sustainable seaweed value chains necessitate accurate biomass biochemical characterisation that lead...

Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [F]-FDG-PET-radiomic features.

OBJECTIVES: This study evaluates the effectiveness of machine learning (ML) models that incorporate ...

Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food.

Zearalenone (ZEN) has been detected in both pet food ingredients and final products, causing acute t...

Deep learning model for low-dose CT late iodine enhancement imaging and extracellular volume quantification.

OBJECTIVES: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (...

Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy a...

A deep learning method for total-body dynamic PET imaging with dual-time-window protocols.

PURPOSE: Prolonged scanning durations are one of the primary barriers to the widespread clinical ado...

Radiomics and Artificial Intelligence Landscape for [F]FDG PET/CT in Multiple Myeloma.

[F]FDG PET/CT is a powerful imaging modality of high performance in multiple myeloma (MM) and is con...

Deep learning for cardiac imaging: focus on myocardial diseases, a narrative review.

The integration of computational technologies into cardiology has significantly advanced the diagnos...

Applicability of creatinine-based glomerular filtration rate assessment equations to patients with neurogenic bladder.

PURPOSE: Glomerular filtration rate (GFR) measured by dynamic renal scintigraphy (Gates method) is u...

AI potential in PET/CT cancer imaging.

Positron emission tomography/computed tomography (PET/CT) is a hybrid medical imaging technique that...

A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.

INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-bas...

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