Latest AI and machine learning research in radiology for healthcare professionals.
PURPOSE OF REVIEW: Urolithiasis management increasingly depends on accurate, noninvasive stone phenotyping to guide acute intervention, secondary prevention, and selective chemolitholysis. Photon-counting computed tomography (PCCT) introduces detector-level energy discrimination and higher spatial resolution, enabling calcium-preserving reconstruction strategies and quantitative spectral analytics...
BACKGROUND: Thyroid carcinoma is the most prevalent endocrine malignancy, with a worldwide increasing incidence. Capsular invasion and neural invasion (NI) are pivotal prognostic factors for recurrence and survival; however, their preoperative noninvasive assessment remains challenging. OBJECTIVE: We aimed to identify computed tomography (CT) radiomic biomarkers associated with capsular invasion i...
BACKGROUND AND PURPOSE: Pediatric low-grade gliomas (pLGGs) are the most common brain tumors in children and frequently harbor BRAF alterations, most ...
In 2025, interventional pulmonology continues to progress rapidly through technological innovation and multidisciplinary integration, playing an incre...
OBJECTIVE: To explore the predictive value of machine learning-based multimodal MRI radiomics combined with clinical features in the efficacy of high-...
The brain age gap (BAG) is defined as the difference between brain age estimated from MRI using artificial intelligence and chronological age, and has...
Machine learning-generated segmentations of the trigeminal nerve and surrounding vasculature can quantitatively assess the magnitude of neurovascular ...
PURPOSE: To improve the quality of a fast multi-contrast MR protocol acquisition using deep learning. MATERIALS AND METHODS: 350 patients (age: 64 ± 1...
Multiparametric Magnetic Resonance Imaging (mpMRI), including T2-weighted imaging (T2), diffusion-weighted imaging (DWI), and dynamic contrast-enhance...
Cell migration underlies immune surveillance, tissue repair, embryogenesis, and-when dysregulated-tumor metastasis. Yet unlike proliferation, which ca...
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound ...
The intratumoral and peritumoral architectural heterogeneities of papillary thyroid carcinoma (PTC) are important in preoperative prediction of gross ...
Various harmonization methods have been employed for obtaining MRI from different scanners. However, no study has yet focused on the clinical utility ...
BACKGROUND: Artificial intelligence-enabled coronary plaque analysis (AI-CPA) has been shown to improve cardiovascular risk prediction. However, littl...
Accurate evaluation of tumor size on follow-up computed tomography (CT) scans is critical for assessing treatment efficacy in cancer patients. However...
This study presents an integrated methodology for pre-operative cryosurgical planning of irregularly shaped brain tumors using two-dimensional MRI dat...
The effective integration of artificial intelligence (AI) systems into clinical medicine depends on comprehensive and transparent performance evaluati...
Artificial intelligence (AI) is increasingly shaping radiology, though its integration into paediatric radiology has progressed more slowly due to cha...