Latest AI and machine learning research in radiology for healthcare professionals.
OBJECTIVE: OpenAI, Google, and Microsoft have recently developed popular large language models (LLMs...
BACKGROUND: Dental caries is the most prevalent chronic, noncommunicable condition affecting individ...
The scarcity of subspecialist medical expertise poses a considerable challenge for healthcare delive...
BACKGROUND: We aimed to develop a novel cardiac magnetic resonance (CMR)-based method for quantifyin...
AIMS: Coronary angiography might contain clinically relevant information, beyond its traditional rol...
AIMS: Catheter-based coronary intervention is an effective treatment for acute coronary syndrome. Ho...
Diffuse interstitial lung diseases (ILDs) represent a complex and heterogeneous group of pulmonary d...
OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This...
OBJECTIVE: Despite advances in mammography screening, some cancers remain undetected, prompting the ...
BACKGROUND: The binary diagnostic approach does not reflect the entire spectrum of metabolic dysfunc...
IMPORTANCE: Large language models (LLMs), a rapidly advancing domain of artificial intelligence (AI)...
The advent of long-axial-field-of-view (LAFOV) PET/CT systems has significantly improved whole-body ...
Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remai...
Artificial intelligence applied to brain magnetic resonance imaging (MRI) holds potential to advance...
Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critic...
Brown adipose tissue (BAT) plays a key role in energy metabolism and cardiometabolic health. Its det...
ConspectusNear-infrared II (NIR-II, 1000-3000 nm), also defined as shortwave infrared (SWIR) imaging...
PURPOSE: This study aimed to develop and validate machine learning models based on quantitative radi...
Acquired Brain Injury (ABI) refers to any post-birth damage to the brain, commonly resulting from tr...
PURPOSE: This study aims to develop and evaluate a fully automated deep learning-driven postprocessi...
Accurate attenuation correction (AC) is essential for quantitative brain positron emission tomograph...