Latest AI and machine learning research in radiology for healthcare professionals.
Diffuse interstitial lung diseases (ILDs) represent a complex and heterogeneous group of pulmonary disorders, requiring a structured, rigorous, and integrated radiologic approach for accurate diagnosis. High-resolution computed tomography (CT) remains the cornerstone examination, enabling precise identification of elementary lesions and their organization into diagnostic imaging patterns that are ...
OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This study introduces auto-LSN, an artificial intelligence (AI)-based algorithm for fully automated LSN quantification, assesses its association with fibrosis stage and its non-inferiority in diagnostic performance for advanced chronic liver disease (ACLD) and cirrhosis compared to the FDA-approved, sem...
OBJECTIVE: Despite advances in mammography screening, some cancers remain undetected, prompting the evaluation of artificial intelligence (AI) as an i...
BACKGROUND: The binary diagnostic approach does not reflect the entire spectrum of metabolic dysfunction associated steatotic liver disease (MASLD. We...
IMPORTANCE: Large language models (LLMs), a rapidly advancing domain of artificial intelligence (AI), are poised to transform administrative, clinical...
The advent of long-axial-field-of-view (LAFOV) PET/CT systems has significantly improved whole-body imaging by providing higher sensitivity and extend...
Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, primar...
Artificial intelligence applied to brain magnetic resonance imaging (MRI) holds potential to advance diagnosis, prognosis and treatment planning for n...
Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critical. Artificial intelligence (AI), including machin...
Brown adipose tissue (BAT) plays a key role in energy metabolism and cardiometabolic health. Its detection typically relies on 18F-FDG PET, which is c...
ConspectusNear-infrared II (NIR-II, 1000-3000 nm), also defined as shortwave infrared (SWIR) imaging, offers reduced light scattering and low tissue a...
PURPOSE: This study aimed to develop and validate machine learning models based on quantitative radiomics parameters extracted from T1-weighted MRI to...
Acquired Brain Injury (ABI) refers to any post-birth damage to the brain, commonly resulting from traumatic events (traumatic brain injury) or non-tra...
PURPOSE: This study aims to develop and evaluate a fully automated deep learning-driven postprocessing pipeline for multiparametric renal MRI, enablin...
Accurate attenuation correction (AC) is essential for quantitative brain positron emission tomography (PET), but it presents a significant challenge f...
Introduction.Focal cortical dysplasia type II (FCD II) is a significant cause of drug-resistant epilepsy, and the full surgical resection of the lesio...
Ultrasound (US)-guided microwave ablation (MWA) has emerged as a promising minimally invasive therapy for both benign and malignant breast tumors. Thi...
The escalating global burden of diseases-including cancer, neurodegenerative, and cardiovascular disorders-poses severe threats to human health and so...
Purpose To develop a digitized integrated feature-based interpretable machine learning classification model to accurately recognize complex thyroid no...
PURPOSE: The global impact of myopia extends far beyond individual ocular health, posing significant challenges to healthcare systems worldwide. Artif...