Latest AI and machine learning research in nuclear medicine for healthcare professionals.
Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, potentially contributing to polycystic ovary syndrome (PCOS). This study integrates computational toxicology and machine learning to delineate the mechanisms linking PET-MP exposure to PCOS pathogenesis. We conducted systematic multi-omics analysis by...
Accurate staging of prostate cancer is essential for guiding therapy and predicting outcomes. Prostate-specific membrane antigen (PSMA) PET/CT has become an established modality for disease assessment, and the PROMISE v2 framework provides standardized criteria for molecular imaging–based TNM (miTNM, molecular imaging TNM) classification. This study investigates the potential of large language mod...
Reducing scan times, radiation dose, and enhancing image quality, especially for lower-performance scanners, are critical in low-count/low-dose PET im...
Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac function, and its measurement can guide treatment decis...
PURPOSE: Vestibular schwannomas are benign tumors of the cerebellopontine angle that may causesignificant neurological morbidity. Magnetic resonance i...
OBJECTIVE: We used deep learning to generate synthetic, resembling in appearance, iodine-enhanced, mammograms from low-energy contrast-enhanced mammog...
BACKGROUND: Iodine-131 (131I) therapy is a cornerstone of nuclear medicine for thyroid diseases and certain cancers. This review evaluates the transit...
OBJECTIVE: Dynamic PET imaging with 11C-UCB-J enables in vivo quantification of synaptic vesicle glycoprotein 2A (SV2A), with prior reports of lower s...
Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting ...
This review explores the revolutionary impact of long axial field-of-view (LAFOV) PET/CT imaging in modern nuclear medicine and molecular imaging. LAF...
PURPOSE OF REVIEW: Urolithiasis management increasingly depends on accurate, noninvasive stone phenotyping to guide acute intervention, secondary prev...
This study introduces SwinPix, a novel network architecture designed to explore the effectiveness of multi-level low-dose (LD) PET inputs as prior kno...
Recent advancements in nuclear medicine, particularly in personalised radiopharmaceutical therapy, have emphasised the growing need for precise assess...
BackgroundAlzheimer's disease (AD) affects 55 million people worldwide, projected to reach 139 million by 2050; yet, most machine learning (ML)-based ...
The aim of this study was to evaluate the performance of an artificial intelligence (AI)-based method for automated segmentation of total metabolic tu...
In the last few years several "universal" interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atom...
Time-of-flight (ToF) in PET improves image quality by enhancing the signal-to-noise ratio, and recent deep learning (DL)-based ToF (DL-ToF) methods fu...
To investigate a non-invasive magnetic resonance imaging (MRI)-based method for detecting amyloid-β (Aβ) protein deposition in different brain regions...
RATIONALE AND OBJECTIVES: To investigate the performance of deep learning image reconstruction (DLIR) at an ultra-low dose of approximately 4.5 mGy fo...